{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Nodal_Analysis.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyO2IG+7bQWFd57yNPoFQ5jY",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Divyanshu-ISM/Oil-and-Gas-data-analysis/blob/master/Nodal_Analysis.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "j3uA_Z2pIduZ",
        "colab_type": "text"
      },
      "source": [
        "#Nodal Analysis With Python\n",
        "\n",
        "Divyanshu vyas | RE/PE | Data Analysis | Deep Learning | Machine Learning\n",
        "\n",
        "dvyas13ad@gmail.com"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bKKEQg0pIaBt",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pMchb58SI2UH",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 318
        },
        "outputId": "1b4704d8-af48-453e-9623-13c0a117cd50"
      },
      "source": [
        "#First Let's Get the IPR dataset. (Source : PetroWiki)\n",
        "\n",
        "ipr = pd.DataFrame({'Pwf':[4000,3500,3000,2500,2000,1500,1000,500,14.7],\n",
        "                    'Q': [0,1999,3094,3902,4512,4963,5275,5458,5519]})\n",
        "\n",
        "ipr"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Pwf</th>\n",
              "      <th>Q</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>4000.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3500.0</td>\n",
              "      <td>1999</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3000.0</td>\n",
              "      <td>3094</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2500.0</td>\n",
              "      <td>3902</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2000.0</td>\n",
              "      <td>4512</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>1500.0</td>\n",
              "      <td>4963</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>1000.0</td>\n",
              "      <td>5275</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>500.0</td>\n",
              "      <td>5458</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>14.7</td>\n",
              "      <td>5519</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      Pwf     Q\n",
              "0  4000.0     0\n",
              "1  3500.0  1999\n",
              "2  3000.0  3094\n",
              "3  2500.0  3902\n",
              "4  2000.0  4512\n",
              "5  1500.0  4963\n",
              "6  1000.0  5275\n",
              "7   500.0  5458\n",
              "8    14.7  5519"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "P2Ttw7VPJhj0",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#Now TPR Data\n",
        "\n",
        "q = np.arange(1000,6500,500)\n",
        "\n",
        "p_190 = [1334,1400,1487,1592,1712,1843,1984,2132,2287,2446,2609]\n",
        "\n",
        "p_2375 = [1298,1320,1351,1390,1435,1487,1545,1609,1677,1749,1824]\n",
        "\n",
        "p_2875 = [1286,1294,1305,1319,1336,1356,1378,1403,1431,1461,1493]\n",
        "\n",
        "tpr = pd.DataFrame({'q':q, 'Pwf(1.90\" tbg)':p_190, 'Pwf(2.375\"tbg)': p_2375,'Pwf(2.875\"tbg)':p_2875})"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Hj0JCX3yLDIF",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 428
        },
        "outputId": "fe453283-70f1-424e-ff25-d71b22856c00"
      },
      "source": [
        "#Let's Plot them now. \n",
        "plt.figure(figsize=(8,4))\n",
        "\n",
        "plt.style.use('default')\n",
        "\n",
        "plt.plot(ipr['Q'], ipr['Pwf'], label = 'IPR', linewidth=1.5)\n",
        "\n",
        "plt.plot(tpr['q'],tpr['Pwf(1.90\" tbg)'],label='TPR for 1.9\" tubing', linewidth=1.5)\n",
        "plt.plot(tpr['q'],tpr['Pwf(2.375\"tbg)'],label='TPR for 2.375\" tubing', linewidth=1.5)\n",
        "plt.plot(tpr['q'],tpr['Pwf(2.875\"tbg)'],label='TPR for 2.875\" tubing', linewidth=1.5)\n",
        "\n",
        "plt.xlabel('FlowRate(Mscf/D)')\n",
        "plt.ylabel('Flowing BHP(Psia)')\n",
        "plt.title('Nodal Analysis for a Gas Well')\n",
        "\n",
        "plt.grid()\n",
        "\n",
        "plt.legend(loc='best')\n"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7f0096fbfeb8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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3+fvvv8vNaJCWllbu+M2aNQO4YRpEcXFxufQBFxcX3NzcbmtVNFdXV5o1a8ayZcsMAvujR4+yadMm/et/O+7kda5Xrx7Dhg3jjz/+4NNPP62wzvXHNjExQaVSGbw+cXFxrF271qBeampquWPdqt+v1aZNG1JSUli6dClPPPGEPs8ZSgPgmJgYfv31VxwdHfUfGk1MTOjTpw+//PJLuVFtoMIp84QQVSMjwEKIKnvrrbf4/vvviYmJMRilbNq0KYMHD+arr74iPT2dtm3bsmfPHpYtW8YzzzxDu3btgNIRrilTpjB37lx69OhBt27dOHDgAH/88Ue50b4ePXowc+ZMhg4dSlBQEEeOHCEsLMxg5Liydu/ezcmTJw2mG7tWnTp1aNGiBWFhYbz++utVOnaPHj34/vvvsbOzw9/fn507d7J582b9NGm3YmZmRr9+/fj0008xMTGhf//+BtuXLVvG4sWLefbZZ6lfvz5ZWVl8/fXXaLXaGwaeWVlZ1K1bl+eff56mTZui0WjYvHkze/fuNRiprooPP/yQrl270qpVK4YPH66fBs3Ozs5g/uGqutPXecGCBZw5c4ZXX32Vn376iZ49e+Li4sKlS5fYsWMH69atM8hd7t69Ox9//DFdunThpZdeIjk5mc8++4wGDRpw+PBhfb2ZM2eyfft2unfvjoeHB8nJySxevJi6devedF7jMmV1du7cWa5/yqY527VrFz179jRIHXrvvffYunUrTzzxBCNHjsTf35/U1FT279/P5s2bKwzMhRBVYKTZJ4QQ94Frp0G73uDBgxXAYBo0RVGUoqIiZcaMGYqXl5diZmamuLu7K2+88YaSn59vUK+4uFiZMWOG4urqqlhZWSnBwcHK0aNHFQ8Pj3LToL322mv6eq1bt1Z27typtG3bVmnbtq2+XmWmQXv11VcVQDl16tQN64SEhCiAcujQIUVRSqcVq2gasevbmZaWpgwdOlRxcnJSNBqN0rlzZ+X48ePl6lU0DVqZPXv2KIDSqVOnctv279+v9O/fX6lXr55iYWGhuLi4KD169FD27dtnUI9rpkErKChQ/vvf/ypNmzZVbG1tFRsbG6Vp06bK4sWLb3j917fz+mnQFEVRNm/erLRu3VqxsrJStFqt0rNnTyUqKsqgTtlUXJWdPqyyr/PNXLlyRVm6dKny9NNPKw4ODoqpqani5OSktG/fXvniiy+UvLw8g/rffPON4uPjo1hYWCgNGzZUli5dWm4Ksb/++kvp3bu34ubmppibmytubm5K//79lRMnTlSqTTk5OYqpqakCKJs2bSq3PSAgQAGU999/v9y2pKQkZezYsYq7u7tiZmam6HQ6pX379spXX32lryPToAlxe1SKcpOZyYUQQtSYQ4cO0axZM7777jsGDhxo7OYIIcQDS3KAhRDiHvH111+j0Wh47rnnjN0UIYR4oEkOsBBCGNm6deuIioriq6++Yty4cbc9k4IQQojKkRQIIYQwMk9PT5KSkujcuTPff/+9fmEHIYQQd4cEwEIIIYQQ4qEiOcBCCCGEEOKhIgGwEEIIIYR4qMhNcJVQUlJCfHw8tra2BhOVCyGEEEKIe4OiKGRlZeHm5maw6mJFJACuhPj4eNzd3Y3dDCGEEEIIcQvnz5+nbt26N60jAXAllN2Rff78ebRabY2cs6ioiE2bNtGpUyfMzMxq5JxC+t0YpM+NQ/rdOKTfjUP63Thqut8zMzNxd3ev1Ew6EgBXQlnag1arrdEA2NraGq1WK2/WGiT9XvOkz41D+t04pN+NQ/rdOIzV75VJV5Wb4IQQQgghxENFAmAhhBBCCPFQkQBYCCGEEEI8VCQHWAghhLhHKYrClStXKC4uNnZT7mtFRUWYmpqSn58vfVmD7ka/m5mZYWJicsfHkQBYCCGEuAcVFhaSkJBAbm6usZty31MUBZ1Ox/nz52U+/xp0N/pdpVJRt25dNBrNHR1HAmAhhBDiHlNSUsKZM2cwMTHBzc0Nc3NzCdzuQElJCdnZ2Wg0mlsukCCqT3X3u6IopKSkcOHCBXx8fO5oJFgCYCGEEOIeU1hYSElJCe7u7lhbWxu7Ofe9kpISCgsLsbS0lAC4Bt2Nfnd2diYuLo6ioqI7CoDvmZ+C9957D5VKxcSJE/Vl+fn5jB07FkdHRzQaDX369CEpKclgv3PnztG9e3esra1xcXHhv//9L1euXDGos23bNlq0aIGFhQUNGjQgNDS0Ji5JCCGEuCMSrAlhqLq+Cbkn3ll79+7lyy+/JCAgwKB80qRJrFu3jpUrV/L3338THx/Pc889p99eXFxM9+7dKSwsJDIykmXLlhEaGsq0adP0dc6cOUP37t1p164dBw8eZOLEiYwYMYKNGzfW2PUJIYQQQoh7h9ED4OzsbAYMGMDXX39NrVq19OUZGRl88803fPzxxzz99NO0bNmSpUuXEhkZya5duwDYtGkTUVFRLF++nGbNmtG1a1dmzZrFZ599RmFhIQBffPEFXl5ezJs3Dz8/P8aNG8fzzz/P/PnzjXK9lRF3KYdfDyWQkAtXikuM3RwhhBBCiAeK0XOAx44dS/fu3enQoQPvvvuuvvzff/+lqKiIDh066MsaNmxIvXr12LlzJ4GBgezcuZMmTZpQu3ZtfZ3OnTszevRojh07RvPmzdm5c6fBMcrqXJtqcb2CggIKCgr0zzMzM4HS6TyKioru+JpvJTwqgdkbYgBTPj66BV+dBj+dLX6utvjpbPHV2aKxMPpL90Aqe31r4nUWpaTPjUP63Tgq2+9FRUUoikJJSQklJTIQcqcURdH/K/1Zc+5Gv5eUlKAoSoU5wFX5fWbUKOqnn35i//797N27t9y2xMREzM3Nsbe3NyivXbs2iYmJ+jrXBr9l28u23axOZmYmeXl5WFlZlTv33LlzmTFjRrnyTZs21cjNCGdTVHjZqonPgYLiEo5czOTIxUyDOk4WCnVsyh5Q11rBzhzkJuHqER4ebuwmPHSkz41D+t04btXvpqam6HQ6srOz9d9o3i/GjBlDRkYGYWFhjBkzhh9//BEonb+1bt269OvXj8mTJ2NqakpERAQ9e/bU7+vo6Ejz5s0JCQmhUaNG1d62rKysaj+muLXq7PfCwkLy8vLYvn17uXu+qjJloNEC4PPnzzNhwgTCw8OxtLQ0VjMq9MYbbzB58mT988zMTNzd3enUqRNarfaun78bpZ9iNm4Kx+/RNsReyiM6IYvoxEyiE7JIzCzgUoGKSwUqDqVe3a+WtZnBSHFDnS3ezjaYmRg90+W+UVRURHh4OB07dsTMzMzYzXkoSJ8bh/S7cVS23/Pz8zl//jwajeae+xt5K2ZmZpiamqLVajEzM6Nz5858++23FBQUsGHDBl599VU0Gg1Tp07VDypFR0ej1WqJj4/n9ddfp3///pw4cQJzc/NqaZOiKGRlZWFrayvTydWgu9Hv+fn5WFlZ8dRTT5V7b5R9Y18ZRguA//33X5KTk2nRooW+rLi4mO3bt/Ppp5+yceNGCgsLSU9PNxgFTkpKQqfTAaDT6dizZ4/Bcctmibi2zvUzRyQlJaHVaisc/QWwsLDAwsKiXLmZmVmN/qFQq6B+bS0N6zrSs9nV8tScQqITMomKzyQqIZPohExik7NJyy0i8nQqkaevRsXmJmoe0Wnwd9WWPtzsaOhqi9ZS/uDdTE2/1kL63Fik343jVv1eXFyMSqVCrVbrZ4JQFIW8oppfxczKzKRKwYtKpdK3XaVSYWlpiZubG1Ca9vjrr7+ybt063nzzTf216XQ67O3tcXNzY+LEifTq1YsTJ06Uuzn+dpV9/V7WLlEz7ka/l/1cVfQeqsrvMqMFwO3bt+fIkSMGZUOHDqVhw4a8/vrruLu7Y2Zmxl9//UWfPn0AiImJ4dy5c7Rq1QqAVq1aMXv2bJKTk3FxcQFKv1bSarX4+/vr62zYsMHgPOHh4fpj3I8cbMxp3cCJ1g2c9GX5RcWcTM7WB8Vl/2YXXOHoxUyOXpdCUc/BGn9XLX6uWvzdSh9udpbyyVgIIe5ReUXF+E+r+RmMomZ2xtq8+sIFKysrLl++XOG2jIwMfvrpJ4BqG/0VoiJGC4BtbW1p3LixQZmNjQ2Ojo768uHDhzN58mQcHBzQarW8+uqrtGrVisDAQAA6deqEv78/AwcO5IMPPiAxMZG3336bsWPH6kdwX3nlFT799FP+7//+j2HDhrFlyxZ+/vlnfv/995q94LvM0syExnXsaFzHTl9WUqJwIS2PqISMa0aLs7iYnse51FzOpeby57FEfX07K7P/jRJr9f/Wd9ZgbiqfloUQQtwZRVH466+/2LhxI6+++qrBtrp16wKQk5MDQK9evWjYsGGNt1E8PO7pqQTmz5+PWq2mT58+FBQU0LlzZxYvXqzfbmJiwvr16xk9ejStWrXCxsaGwYMHM3PmTH0dLy8vfv/9dyZNmsTChQupW7cuS5YsoXPnzsa4pBqlVquo52hNPUdrujR21Zen5xYajBJHxWdyMjmbjLwidp6+zM7TVz+Zm5uoaeCiMQiK/Vy12FnJV6ZCCFGTrMxMiJpZ83+7rMxuf7UtgPXr16PRaCgqKqKkpISXXnqJkJAQgzr//PMP1tbW7Nq1izlz5vDFF1/c0TmFuJV7KgDetm2bwXNLS0s+++wzPvvssxvu4+HhUS7F4XrBwcEcOHCgOpr4QLC3NieovhNB9a+mUBRcKSY2Kbs0t/ia4Dgr/0rp8wTDFIq6tawMRov9XLXUrWUlKRRCCHGXqFSqak1FqCnt2rXj888/x9zcHDc3N0xNy1+Dl5cX9vb2+Pr6kpyczIsvvsj27duN0FrxsLj/3knirrAwLZ9CoShlKRSGo8UX0/O4kFb62BR19QZDraXp1Zzi//3r42IrKRRCCPEQs7GxoUGDBpWuP3bsWObOncuaNWt49tln72LLxMNMAmBxQyqVCncHa9wdrOncSKcvz8gtIjrRMCiOTc4iM/8Ku8+ksvvM1VkozExUNHCx/d8osa0+OLa3lpsbhBBClGdtbc3IkSOZPn06zzzzjHyzKO4KCYBFldlZmxHo7Uigt6O+rPBKSeksFPrR4tIb7zLzrxD9v6narlXH3spgtLiRm6RQCCGEKDVu3Dg+/vhjVq5cyQsvvGDs5ogHkATAolqYm6r106nRsrRMURTiM/JLA+KyoDghk/OpeVxML31sjr6aQmFrUUEKRW0NFqZ3dgOGEEKImhMaGlrh/ysSHBysXy73Wu7u7rJMt7irJAAWd41KpaKOvRV17K3o6H91OeqMvCKOJ1xdxCMqIZMTidlkFVxhT1wqe+KuplCYqlWls1Bcd8NdLRtJoRBCCCHE7ZEAWNQ4OysznvB25IlrUiiKiks4lZJ9zWhx6SM9t4jjiVkcT8xi9YGL+vqudpbl5ix2r2WNWi0pFEIIIYS4OQmAxT3BzERNQ52Whjotz/1vdWxFUUjIyDdY9jkqIZOzl3NJyMgnISOfv44n64+hsTAtvdHumhXuHqlti+UdzmEphBBCiAeLBMDinqVSqXCzt8LN3or2fldTKLLyS0eFrx0tjknKIrvgCnvj0tgbl6ava6JWUd/Z5prRYjv8XG1x1FgY45KEEEIIcQ+QAFjcd2wtzXjM04HHPB30ZUXFJZxOyTFYyONYfAZpuUWcSMrmRFI2aw/G6+vrtJbXTMtmh7+bFg8Ha2NcjhBCCCFqmATA4oFgZqLGV2eLr86WZ5rXAUpTKJIyC/RTspXedJfFmUs5JGbmk5iZz9aYFP0xrM1NaKizxbpATda+CzSpWwtfnaRQCCGEEA8aCYDFA0ulUqGzs0RnZ8nTDa+mUGQXXCHmuoU8jidmkVtYzP5z6YCaiF+jAFCrwNtZU+6GOydJoRBCCCHuWxIAi4eOxsKUlh4OtPS4mkJxpbiEM5dyOHw+jQ2RhyiwdiY6IYvLOYWcTM7mZHI2vx26mkLhYmthMC2bv5sWT0cbTGQWCiGEEOKeJwGwEICpiRqf2rZ4OlhievEA3bq1xNTUlJSsAo5dMwtFdHwmZy7nkJxVQHJMCtuuSaGwMjOh4f9moSgLjhvqtFiZSwqFEEIIcS+RAFiIG1CpVLhoLXHRWtLO10VfnlNwheOJWQY33B1PzH4SXr4AACAASURBVCSvqJgD59I5cC5dX1etAi8nm3Ir3LnYWhrjkoQQ4oGVm5vLwIEDCQ8PJysri7S0NOzt7Y3drHuCSqVizZo1PPPMMxVuj4uLw8vLiwMHDtCsWbMabp1xSAAsRBXZWJjS0qMWLT1q6cuKSxTOXMrRB8Rl/17KLuBUSg6nUnJYfzhBX99JY2EQEPu7avFykhQKIcT9S6W6+e+v6dOnM2TIELy8vPRlDg4OtGzZkvfff5/mzZsDpcsj//333wBYWFhQr149hg4dytSpU296jmXLlvHPP/8QGRmJk5MTdnZ21XBVV40fP54dO3Zw9OhR/Pz8OHjw4C33OXXqFFOmTCEiIoKCggK6dOnCokWLqF376n0pKpWKM2fOsG3bNkJDQ9m2bVuFx9q2bRvt2rW7K4G9u7s7CQkJODk5Vetx72USAAtRDUz+t2RzAxcNvZq66cuTs/KJTsi6JijO4PSlHC5lF7D9RArbT1xNobA0U+Or016XQmGLjYW8TYUQ976EhKsf8lesWMG0adOIiYnRl2k0Gi5dugTA5s2badSoERcuXGD8+PF07dqV48eP6wO7kSNHMnPmTAoKCtiyZQujRo3C3t6e0aNH3/D8p06dws/Pj8aNG9/2NRQXF6NSqVCr1RVuHzZsGLt37+bw4cO3PFZOTg6dOnWiadOmbNmyBYB33nmHnj17smvXrhuewxhMTEzQ6XTGbkaNund6X4gHkIutJW0fcWZ0cH0W9W/OX68Fc2xGZ9aMCWL2s40Z8EQ9mtezx8rMhPyiEg6dT+fHPed4Z+1R+nweSeOQjTz90TbG/rCfz7aeZGtMMkmZ+SiKYuxLE0LUNEWBwpyaf1Ty941Op9M/7OzsSmfiuaZMo9Ho6zo6OqLT6Xj00Uf56KOPSEpKYvfu3frt1tbW6HQ6PDw8GDp0KAEBAYSHh9/w3MHBwcybN4/t27ejUqkIDg4GIC0tjUGDBuHo6IibmxvdunUjNjZWv19oaCj29vb89ttv+Pv7Y2Fhwblz5yo8xyeffMLYsWPx9vauVH/s2LGDuLg4QkNDadKkCU2aNGHZsmXs27dPHxBXVlxcHO3atQOgVq1aqFQqhgwZAoCnpycLFiwwqN+sWTNCQkIMyhISEujatStWVlZ4e3uzatUqg+OrVCr9qPa2bdtQqVT89ddfPProo1hbWxMUFGTwgQbg3XffxcXFBVtbW0aMGMHUqVPvmxQKGVoSooZZm5vSvF4tmtczTKE4e7l8CkVyVgGnL+Vw+lIOv1+TQuFoY15hCoWpiXymFeKBVZQLc9xuXa+6vRkP5jZ37fBWVlYAFBYWltumKAoREREcP34cHx+fGx5j9erVTJ06laNHj7J69WrMzc0BGDJkCLGxsaxduxa1Ws27775Lt27diIqKwszMDCjNHX7//fdZsmQJjo6OuLi43PA8VVFQUIBKpcLC4uq0mZaWlqjVaiIiIujQoUOlj+Xu7s4vv/xCnz59iImJQavV6vutst555x3ee+89Fi5cyPfff0+/fv04cuQIfn5+N9znrbfeYt68eTg7O/PKK68wbNgwduzYAUBYWBizZ89m8eLFtG7dmp9++ol58+YZpLjcyyQAFuIeYKJW4e2swdtZQ4+Aq3/gUrIK9DfbRf8vKD6Vks3lnEL+ib3EP7GX9HUtTNU01JWubufn+r8UClctGkmhEELco9LT05k1axYajYbHH39cX7548WKWLFlCYWEhRUVFWFpaMn78+Bsex8HBAWtra8zNzfVf5cfGxvLbb7+xY8cOAgMDyczMZPny5Xh4eLB27Vr69u0LQFFREYsXL6Zp06bVem2BgYHY2Njw+uuvM2fOHBRFYerUqRQXFxuki5R9ozdkyBD9qO71TExMcHAonbrTxcXltnKA+/bty4gRIwCYNWsW4eHhLFq0iMWLF99wn9mzZ9O2bVsApk6dSvfu3cnPz8fS0pJFixYxfPhwhg4dCsC0adPYtGkT2dnZVW6bMchfRiHuYc62FjjbOvPUI876svyiYmISswxGi6MTMsktLObQhQwOXcgwOIano/V1o8V21NZa3PKGFSHEPcbMunQ01hjnrWZBQUGo1WpycnLw9vZmxYoVBjeGDRgwgLfeeou0tDSmT59OUFAQQUFBVTpHdHQ0pqamPPHEE/oyR0dHfH19iY6O1peZm5sTEBBw5xd1HWdnZ1auXMno0aP55JNPUKvV9O/fnxYtWhgl/7dVq1blnt/qRr5r+8XV1RWA5ORk6tWrR0xMDGPGjDGo//jjj1c5vcNYJAAW4j5jaWZCU3d7mrpfHQEoKVE4m5pLVHymwfRsiZn5xF3OJe5yLhuOJOrrO9iY42cwZ7Ed3s42mEkKhRD3LpXqrqYi1KQVK1bg7++Po6NjhaOZdnZ2NGjQAICff/6ZBg0aEBgYWKW0gcqysrK6awMCnTp14tSpU1y6dAlTU1Ps7e3R6XSVziOuDLVaXe6+kKKiomo5dlmaCFyd5aOkpKRajm1sEgAL8QBQq1V4Odng5WRD9wBXffnl7ILSWSgSMvSjxadSckjNKWTHycvsOHlZX9fcVI1v7WuCYrfSWShsLc0qOqUQQtw2d3d36tevX6m6Go2GCRMmMGXKFA4cOFDpYNXPz48rV66we/duAgMDAbh8+TIxMTH4+/vfdttvR9n0Ylu2bCE5OZlevXpV+Rhlec3FxcUG5c7OzgYpFZmZmZw5c6bc/rt27WLQoEEGz8umnrsdvr6+7N271+CYe/fuve3j1TQJgIV4gDlqLGjjY0Ebn6tzO+YXFROblG0QFEcnZJFdcIUjFzM4ctEwhaKeg7XBzXb+blpc7SwlhUIIUWP+85//MGvWLH755Reef/75Su3j4+ND7969GTlyJJ9//jkqlYrZs2dTp04devfuXeU2nDx5kuzsbBITE8nLy9OnD/j7+2Nubs7Fixdp37493333nT6feenSpfj5+eHs7MzOnTuZMGECkyZNwtfXt8rn9/DwQKVSsX79erp164aVlRUajYann36a0NBQevbsib29PdOmTcPEpPwKpCtXruTRRx+lTZs2hIWFsWfPHr755psqt6PMq6++ysiRI3n00UcJCgpixYoVHD58uFpHt+8mCYCFeMhYmpnQpK4dTepenSS+pEThfFquwQwU0QmZxGfkcy41l3Opufx57GoKhb21WWkw7KrVr3LXwEUjKRRCiLvCwcGBQYMGERISwnPPPVfpHNqlS5cyYcIEevXqRWFhIU8++SQbNmww+Gq/skaMGKFfoAPQj56eOXMGT09PioqKiImJITc3V18nJiaGN954g9TUVDw9PXnrrbeYNGlSlc8NUKdOHWbMmMHUqVMZOnQogwYNIjQ0lDfeeIMzZ87Qo0cP7OzsmDVrVoUjwDNmzOCnn35izJgxuLq68uOPP97RSPiAAQM4ffo0U6ZMIT8/nxdeeIEhQ4awZ8+e2z5mTVIpRpxQ9PPPP+fzzz8nLi4OgEaNGjFt2jS6du0KGK4GU+Y///kPX3zxhf75uXPnGD16NFu3bkWj0TB48GDmzp2LqenV2H7btm1MnjyZY8eO4e7uzttvv33DOy0rkpmZiZ2dHRkZGWi12tu/4CooKipiw4YNdOvW7bbeqOL2SL8bSsspNMgpjkrIJDY5m+KS8r82zE3U+NTWGIwW+7lp0d4ihUL63Dik342jsv2en5/PmTNn8PLywtJSlk6/UyUlJWRmZqLVau+pBSgeNB07dkSn0/H9998Dd6ffb/beqEq8ZtQR4Lp16/Lee+/h4+ODoigsW7aM3r17c+DAARo1agRcXQ2mjLX11btRi4uL6d69OzqdjsjISBISEhg0aBBmZmbMmTMHKP1k1r17d1555RXCwsL466+/GDFiBK6urnTu3LlmL1iI+0wtG3OCGjgR1MAwheJkcvbV0eKETKLjM8kquMKx+EyOxWfCv1eP4e5ghZ/OMIWijv3du+lECCHE3Zebm8sXX3xB586dMTEx4ccff2Tz5s03XbDkXmLUALhnz54Gz2fPns3nn3/Orl279AFw2WowFdm0aRNRUVFs3ryZ2rVr06xZM2bNmsXrr79OSEgI5ubmfPHFF3h5eTFv3jygNCk+IiKC+fPnSwAsxG2wNDOhcR07Gte5mkKhKAoX0vI4dl0KxcX0PM6nlj42RSXp62stTfWzT/jWtiY1B1ndTggh7iMqlYoNGzYwe/Zs8vPz8fX15ZdffrkrM3XcDfdMDnBxcTErV64kJyfHYK66sLAwli9fjk6no2fPnrzzzjv6UeCdO3fSpEkTg7kDO3fuzOjRozl27BjNmzdn586d5V6Mzp07M3HixBu2paCggIKCAv3zzMxMoPSrq+qaWuRWys5TU+cTpaTfb5/O1gydryPtfR31Zem5RcQkZRGVkEV0YhbRCVmcTM4mM/8Ku06nsut06v9qmvLD+X/o3sSVbo11NNRpZIT4LpOfdeOobL8XFRWhKAolJSUPzLRTxlT2AbusT8Wds7CwYNOmTeXKr+3fu9HvJSUlKIpCUVFRuZv9qvL7zOgB8JEjR2jVqhX5+floNBrWrFmjT8p+6aWX8PDwwM3NjcOHD/P6668TExPD6tWrAUhMTDQIfgH988TExJvWyczMJC8vr8KlBOfOncuMGTPKlW/atMkgBaMm3C9fJTxopN+rV22gtiUEe8EVD0jMg4s5qtJHroqz2XA+LZ8vtp/hi+1nqG2l0NxRoYVTCbWrttqnqCL5WTeOW/W7qakpOp2O7OzsCpcIFrcnKyvL2E14KFVnvxcWFpKXl8f27du5cuWKwbZrb0C8FaMHwL6+vhw8eJCMjAxWrVrF4MGD+fvvv/H392fUqFH6ek2aNMHV1ZX27dtz6tSpSs8feDveeOMNJk+erH+emZmJu7s7nTp1qtGb4MLDw+nYsaPcoFKDpN9rXlFREev/DMfEPYA/oy7xd+wlkvJK+POCij8vqGlYW0P3Jjq6NdFRz6FmP4A+yORn3Tgq2+/5+fmcP38ejUYjN8FVA0VRyMrKwtbWVr5dqkF3o9/z8/OxsrLiqaeeqvAmuMoyegBsbm6uX+2lZcuW7N27l4ULF/Lll1+Wq1u2nOHJkyepX78+Op2u3HQbSUmleYZlecM6nU5fdm0drVZb4egvlA7rW1hYlCs3MzOr8T8UxjinkH6vaRYm0K1ZXfo85kVWfhHhUUmsOxTPP7GXOJ6UzfGkk8zbfJKAunb0DHCje4ArbvYyNFwd5GfdOG7V78XFxahUKtRqtcxaUA3Kvn4v61NRM+5Gv6vValQqVYXvoar8LjN6AHy9kpISg/zba5VNOl22HnWrVq2YPXs2ycnJuLi4AKVfK2m1Wn0aRatWrdiwYYPBccLDw8utiS2EuDfYWprxXIu6PNeiLum5hWw8lsi6QwlEnrrE4QsZHL6QwewN0TzqUYseAa50C3DFxVZGyIQQQlSeUQPgN954g65du1KvXj2ysrL44Ycf2LZtGxs3buTUqVP88MMPdOvWDUdHRw4fPsykSZN46qmnCAgIAErX2Pb392fgwIF88MEHJCYm8vbbbzN27Fj9CO4rr7zCp59+yv/93/8xbNgwtmzZws8//8zvv/9uzEsXQlSCvbU5Lz5Wjxcfq0dKVgF/Hk1g3eEE9salsu9sGvvOpjFzfRRPeDnSo6krXRu74mBjbuxmCyGEuMcZNQBOTk5m0KBBJCQkYGdnR0BAABs3bqRjx46cP3+ezZs3s2DBAnJycnB3d6dPnz68/fbb+v1NTExYv349o0ePplWrVtjY2DB48GCDeYO9vLz4/fffmTRpEgsXLqRu3bosWbJEpkAT4j7jbGvBwFaeDGzlSWJGPr8fSWD94XgOnEtn5+nL7Dx9mWm/HqN1Ayd6BrjSqZEOOyv5al8IIUR5Rg2Ab7YGtbu7e7lV4Cri4eFRLsXhesHBwRw4cKDK7RNC3Jt0dpYMb+PF8DZenE/N5fcjCaw7FM+x+Ey2n0hh+4kU3lpzlKcecaZnU1c6+NXGxuKey/gSQlSj3NxcBg4cSHh4OFlZWaSlpWFvb2/sZj0wgoODadasGQsWLLhhHU9PTyZOnHjTqWbvFZIJLoS4r7k7WPNK2/r8Pv5JtrzWlskdH+GR2hoKi0vYHJ3EhJ8O0mJWOGPC/mXDkQTyi4qN3WQhHkgqleqmj5CQEOLi4gzKHB0d6dSpk8EgVXBwsH67paUljzzyCHPnzr3lYjnLli3jn3/+0a8Ma2dnd9P6VXHo0CH69++Pu7s7VlZW+Pn5sXDhwlvu16tXL+rVq4elpSWurq4MHDiQ+Ph4/faQkJAK+8rGxkZfJzQ0tNz262c/CA4OJjQ0VN+/N6NSqVi7dm0Ve6By9u7dazCD171MhkSEEA8Mb2cN49v7ML69DzGJWaw/HM/6wwmcuZTDhiOJbDiSiI25CR38a9MzwI0nH3HCwtTk1gcWQtxSQkKC/v8rVqxg2rRpxMTE6Ms0Gg2XLl0CYPPmzTRq1IgLFy4wfvx4unbtyvHjx/UjtiNHjmTmzJkUFBSwZcsWRo0ahb29PaNHj77h+U+dOoWfnx+NGze+7Wu4dvaNa/3777+4uLiwfPly3N3diYyMZNSoUZiYmDBu3LgbHq9du3a8+eabuLq6cvHiRaZMmcLzzz9PZGQkAFOmTOGVV14x2Kd9+/Y89thjBmVardagL+/VqdycnZ2N3YRKkxFgIcQDyVdny2udfNnyWlvWv9qG/7T1po69FTmFxfx6MJ4R3+3j0Xc3M2XlIf4+kUJRsawOJe5tiqKQW5Rb44/KLlOu0+n0Dzs7O1QqlUGZRqPR13V0dESn0/Hoo4/y0UcfkZSUxO7du/Xbra2t0el0eHh4MHToUAICAm66eEhwcDDz5s1j+/btqFQqgoODAUhLS2PQoEE4Ojri5uZGt27diI2N1e8XGhqKvb09v/32G/7+/lhYWHDu3Llyxx82bBgLFy6kbdu2eHt78/LLLzN06FD9wlw3MmnSJAIDA/Hw8CAoKIipU6eya9cu/YplGo3GoI+SkpKIiopi+PDhBse5vi+vX+Crsjw9PQF49tlnUalU+udDhgzhmWeeMag7ceJEfT+WuXLlCuPGjcPOzg4nJyfeeecdg58PT09PgxQJExMTvvvuO5577jmsra3x8fHht99+Mzjmb7/9ho+PD5aWlrRr145ly5ahUqlIT0+/rWusLBkBFkI80FQqFY3r2NG4jh1TuzTkwPl01h9K4Pcj8SRlFrDq3wus+vcCtazN6NrElR4Brjzh5YiJ+t4cYREPr7wreTzxwxM1ft7dL+3G2uzuLUJTNid/RSveKYpCREQEx48fx8fH54bHWL16NVOnTuXo0aOsXr0ac/PS2WCGDBlCbGwsa9euRa1W8+6779KtWzeioqL0c8bm5uby/vvvs2TJEhwdHfXTqt5KRkYGDg4Olb7O1NRUwsLCCAoKuuF8tUuWLOGRRx7hySefNCjPzs7Gw8ODkpISWrRowZw5c2jUqFGlz11m7969uLi4sHTpUrp06VJuKeFbWbZsGcOHD2fPnj3s27ePUaNGUa9ePUaOHHnDfd5//30++OADPvroIxYtWsSAAQM4e/YsDg4OnDlzhueff54JEyYwYsQIDhw4wJQpU6p8XbdDAmAhxENDpVLRol4tWtSrxdvd/dgbl8q6w/H8cSSRyzmF/LD7HD/sPoezrQXdm7jSs6krzd1roZZgWIi7Ij09nVmzZqHRaHj88cf15YsXL2bJkiUUFhZSVFSEpaUl48ePv+FxHBwcsLa2xtzcXL8QVmxsLL/99hs7duwgMDCQzMxMli9fjoeHB2vXrqVv375A6ep8ixcvpmnTppVud2RkJCtWrKjUlKqvv/46n376Kbm5uQQGBrJ+/foK6+Xn5xMWFsbUqVMNyn19ffn2228JCAggIyODjz76iKCgII4dO0bdunUB2LZtm77+zUbsy1IU7O3t9f1UFe7u7syfPx+VSoWvry9Hjhxh/vz5Nw2AX3rpJfr3749arWbOnDl88skn7Nmzhy5duvDll1/i6+vLhx9+qL/Wo0ePMnv27Cq3raokABZCPJTUahVPeDvyhLcjIT0bset0KusOxfPnsURSsgoIjYwjNDIONztLuge40rOpG03q2N2zuXfiwWdlasXul3bfuuJdOG91CwoKQq1Wk5OTg7e3NytWrDD4Wn/AgAG89dZbpKWlMX36dIKCgggKCqrSOaKjozE1NdWvIgulqRe+vr5ER0fry8zNzfXrC1TG0aNH6d27N9OnT6dTp063rP/f//6X4cOHc/bsWWbMmMGgQYNYv359ud8la9asISsri8GDBxuUt2rVymDxrqCgIPz8/Pjyyy+ZNWtWpdtdHQIDAw3a3apVK+bNm0dxcfENR5OvHam2sbFBq9WSnJwMQExMTLl852s/CN1NEgALIR56piZq2vg40cbHiVnPNCbiZArrDyWwKSqJ+Ix8vv7nDF//c4Z6Dtb0bOpKjwA3Guqqb217ISpDpVLd1VSEmrRixQr8/f1xdHSscKoyOzs7GjRoAMDPP/9MgwYNCAwMpEOHDtXeFisrq0q/l6Oiomjfvj2jRo0yWJfgZpycnHBycuKRRx7Bz88Pd3d3du3aVW5F2iVLltCjR49b5veamZnRvHlzTp48WanzV4ZarS43clyWp3ynrk/3UKlU+iWSjUlughNCiGuYm6p5umFtPn6xGfve7sAXL7ekR4ArVmYmnEvN5bOtp+i68B86zt/Ogs0nOJmcbewmC3HfcXd3p379+pWap1ej0TBhwgSmTJlS6RvyAPz8/Lhy5YrBzXWXL18mJiYGf3//Krf52LFjtGvXjsGDB9/2V/RlgV9BQYFB+ZkzZ9i6dWu5m98qUlxczJEjR3B1db2tNpiZmVFcbDgdpLOzs8EsHgAHDx4st++1fQmwa9cufHx8qpxLXMbX15d9+/YZlO3du/e2jlVVEgALIcQNWJqZ0KWxjk9fasG/73RgUf/mdPKvjbmpmpPJ2SzYHEuHj/+m68J/+GzrSc5dzjV2k4V4IP3nP//hxIkT/PLLL5Xex8fHh969ezNy5EgiIiI4cuQIAwcOpE6dOvTu3btK5z969Cjt2rWjU6dOTJ48mcTERBITE0lJSdHX2bNnDw0bNuTixYtAabD46aefcvDgQc6ePcuWLVvo378/9evXLzf6++233+Lq6krXrl3LnXvmzJls2rSJ06dPs3//fl5++WXOnj3LiBEjqnQNZTw9Pfnrr79ITEwkLS0NgKeffpp9+/bx3XffERsby/Tp0zl69Gi5fc+dO8fkyZOJiYnhxx9/ZNGiRUyYMOG22gGlr+vx48d5/fXXOXHiBD///DOhoaHA3Z/qTQJgIYSoBGtzU3o2deOrQY+y7+0OzOvblHa+zpiqVUQnZPLhxhie+nArvT+NYMk/p4lPzzN2k4V4YDg4ODBo0CBCQkKq9PX50qVLadmyJb169aJz584oisKGDRtuOAvDjaxatYqUlBSWL1+Oq6ur/nFt/mpubi4xMTH61AFra2tWr15N+/bt8fX1Zfjw4QQEBPD3339jYWGh36+kpITQ0FCGDBlS4UhqWloaI0eOxM/Pj27dupGZmUlkZORtjWIDzJs3j/DwcNzd3WnevDkAnTt35p133uH//u//eOyxx8jKymLQoEHl9h00aBB5eXk8/vjjjB07lgkTJtzRwhdeXl6sWrWK1atXExAQwOeff85bb70FYNBHd4NKqcr3CQ+pzMxM7OzsyMjIQKvV1sg5i4qK2LBhA926davyG1XcPun3mne/93laTiEbjyWy/nACkacuUXLNb9RHPWrRs6kbXZvocLG1vPFBjOB+7/f7VWX7PT8/nzNnzuDl5VVu1S9RdSUlJWRmZqLVasstciHuntvp99mzZ/PFF19w/vz5Crff7L1RlXhNboITQog7UMvGnH6P16Pf4/VIySrgz6MJrDuUwN6zqew7m8a+s2nMWHeMQG9HegS40aWxDgcbc2M3Wwgh7gmLFy/msccew9HRkR07dvDhhx/edHW96iIBsBBCVBNnWwsGtvJkYCtPEjPy+f1IAusOxXPwfDqRpy4Teeoy0349SusGTvQIcKVTIx12VjL6KoR4eMXGxvLuu++SmppKvXr1eO2113jjjTfu+nklABZCiLtAZ2fJ8DZeDG/jxfnUXNYfTmD94XiOxWfy94kU/j6RwltrjvLUI870bOpKB7/a2FjIr2QhxMNl/vz5zJ8/v8bPK79thRDiLnN3sGZ0cH1GB9fndEo26w+XjgzHJmezOTqJzdFJWJqpad+wNj0CXGnX0AVLs9ubVkgIIcStSQAshBA1yNtZw/j2Poxv70NMYhbrD8ez7lA8cZdz+f1IAr8fScDG3ISO/rXpEeDGk484YWEqwbAQQlQnCYCFEMJIfHW2+Op8mdzxEY7FZ7LucDzrDyVwMT2PtQfjWXswHq2lKZ0b6ejZ1I2g+o6Ymsgd7EIIcackABZCCCNTqVQ0rmNH4zp2TO3SkAPn01l3KJ7fDyeQnFXAyn8vsPLfCzjYmNOlsY6eAW487uWAiVqWYhZCiNshAbAQQtxDVCoVLerVokW9Wrzd3Z+9camsPxzPhiOJpOYU8sPuc/yw+xzOthZ0b+JKz6auNHevhVqCYSGEqDQJgIUQ4h5lolYR6O1IoLcjIT0bsfP0ZdYfSuCPowmkZBUQGhlHaGQcbnaW9GjqRo8AV5rUsbvrS4gKIcT9TpLJhBDiPmBqouZJH2fefz6AfW935Nshj/Js8zpoLEyJz8jnq+2n6fXpDoI/2saHG48TnZCJLPQpHia5ubn06dMHrVaLSqUiPT3d2E16oAwZMoRnnnnmpnWCg4OZOHFiDbXozkgALIQQ9xlzUzVPN6zN/Bebse/tDnzxcku6B7hiaabm7OVcPtt6iq4L/6Hj/O0s2HyCUynZxm6yeAioVKqb4EOzRQAAIABJREFUPkJCQoiLizMoc3R0pFOnThw4cEB/nODgYP12S0tLHnnkEebOnXvLD3TLli3jn3/+ITIykoSEBOzs7Krt2g4dOkT//v1xd3fHysoKPz8/Fi5ceMv9Tpw4Qe/evXFyckKr1dKmTRu2bt2q3x4aGnrD/kpOTgZg27ZtFW5PTEzUH2fIkCGEhIQApa9DXFzcDdvk6enJggULbq8jbmH16tXMmjXrrhy7ukkKhBBC3McszUzo0lhHl8Y6cgqu8NfxZNYfimdbTAonk7NZsDmWBZtj8XPV0rOpKz0D3HB3sDZ2s8UDKCEhQf//FStWMG3aNGJiYvRlGo2GS5cuAbB582YaNWrEhQsXGD9+PF27duX48ePY29sDMHLkSGbOnElBQQFbtmxh1KhR2NvbM3r06Bue/9SpU/j5+dG4cePbvobi4mJUKhVqteH44L///ouLiwvLly/H3d2dyMhIRo0ahYmJyU2X7e3Rowc+Pj5s2bIFKysrFixYQI8ePTh16hQ6nY4XX3yRLl26GOwzZMgQ8vPzcXFxMSiPiYlBq9Xqn1+//V7g4OBg7CZUmowACyHEA8LGwpReTd34atCj7HunA/P6NiXY1xlTtYrohEw++DOGJz/YSu9PI/h2RxzpBcZusagKRVEoyc2t8UdlU2l0Op3+YWdXmot+bZlGo9HXdXR0RKfT8eijj/LRRx+RlJTE7t279dutra3R6XR4eHgwdOhQAgICCA8Pv+G5g4ODmTdvHtu3b0elUhEcHAxAWloagwYNwtHRETc3N7p160ZsbKx+v9DQUOzt7fntt9/w9/fHwsKCc+fOlTv+sGHDWLhwIW3btsXb25uXX36ZoUOHsnr16hu26dKlS8TGxjJ16lQCAgLw8fHhvffeIzc3l6NHjwJgZWVl0EcmJiZs2bKF4cOHlzuei4uLQd3rg/TKCA4O5uzZs0yaNEk/kgwQEhJCs2bNDOouWLAAT0/P/2fvzuOiKvcHjn9mYGAY9h2URXBBwX1Hb2pXxdRc0lYrLTOTa1baTSutm5l561Ze789cysoWrastZso10VxSccldUdzFhU1W2YaBOb8/BgYG0ECBcfm+X695MefMM+d853GQ7zzzfZ5T5RgzZ87E29sbFxcXJkyYQFFRkcXxK5ZAhIaG8uGHH/LMM8/g7OxMUFAQn3zyicXxduzYQfv27dFqtXTu3JlVq1ahUqk4cOBArV9fbVh1BHjhwoUsXLjQPFQfERHBm2++ycCBAwEoLCzk5Zdf5rvvvkOv1zNgwAAWLFiAr6+v+RiJiYlER0ezadMmnJycGDNmDHPmzMHWtvylbd68mSlTpnD06FECAwOZMWMGTz31VEO+VCGEaFAuWg0jOwUwslMAmXlFrDuazJpDl4k7nc7Bi9kcvJgN2PJL+m6GtGvMwDZ++DhrrR22uA6loICEjp0a/Lxh+/ai0tXftwYODg4AFolUGUVR2LZtG8ePH6d58+bXPMaPP/7Iq6++ypEjR/jxxx+xs7MDTKOpJ0+eZNWqVajVat555x0GDRpEfHw8Go0GMNUOv/feeyxZsgRPT88aj6xmZ2dfd8TT09OTsLAwvvrqKzp27Ii9vT2LFy/Gx8eHTp2q/3f86quv0Ol0PPjgg1Uea9++PXq9ntatW/PWW2/Rs2fPGsVZ0Y8//ki7du0YP348zz77bK2fv3HjRrRaLZs3b+bcuXM8/fTTeHp6Mnv27Gs+5+OPP2bWrFlMnz6d77//nujoaHr37k1YWBg5OTkMGTKEQYMGsXz5cs6fP99gNcRWTYADAgL45z//SfPmzVEUhS+//JJhw4axf/9+IiIimDx5MmvXrmXlypW4urry/PPPM2LECLZv3w6YvqoYPHgwfn5+5pqf0aNHo9FoePfddwE4e/YsgwcPZsKECSxbtoyNGzcybtw4/P39GTBggDVfvhBCNAh3Rzse6xrEY12DSLuq539Hklh94BJ/nM8y32b+cpTuoZ7c37YRA1v74e5oZ+2wxV0gKyuLWbNm4eTkRNeuXc37FyxYwJIlSygqKsJgMKDVannhhReueRwPDw90Oh12dnb4+fkBcPLkSVavXs327dvp3r07OTk5fPPNNwQHB7Nq1SoeeughAAwGAwsWLKBdu3Y1jnvHjh3897//Ze3atddso1Kp2LBhA8OHD8fZ2Rm1Wo2Pjw/r1q3D3d292ud89tlnjBo1yvyhAMDf359FixbRuXNn9Ho9S5YsoU+fPuzatYuOHTsCppHsMtcbsffw8MDGxgZnZ2dzP9WGnZ0dn3/+OTqdjoiICN5++21eeeUVZs2adc0R6f79+xMdHY1arWbatGnMnTuXTZs2ERYWxvLly1GpVHz66adotVrCw8O5dOnSDSXntWXVBHjIkCEW27Nnz2bhwoXs3LmTgIAAPvvsM5YvX85f//pXAL744gtatWrFzp076d69O+vXryc+Pp4NGzbg6+tL+/btmTVrFtOmTeOtt97Czs6ORYsWERISwocffghAq1at2LZtG3PnzpUEWAhx1/F2tmd0ZBMe69yY5T/FoPeNIOZICgcuZLHjdDo7Tqfz5s9H6NnMiyHtGhEV4YuLVmPtsAWgcnAgbN9eq5y3rvXo0QO1Wk1eXh6hoaH897//tfh29/HHH2f69OlkZmbyj3/8gx49etCjR49anePYsWPY2trSrVs3876yUdljx46Z99nZ2dG2bdsaH/fIkSMMGzaMf/zjH0RFRV2znaIoTJw4ER8fH37//XccHBxYsmQJQ4YMYc+ePfj7+1u0j4uL49ixY3z99dcW+8PCwggLCzNv9+jRg9OnTzN37twqbetbu3bt0FX4NiAyMpLc3FwuXLhAcHBwtc+JiIgw3y8riymb4JeQkEDbtm3Rasu/far4Qag+3TKT4EpKSli5ciV5eXlERkayd+9eDAYD/fr1M7dp2bIlQUFBxMXF0b17d+Li4mjTpo3FL82AAQOIjo7m6NGjdOjQgbi4OItjlLW53hC7Xq9Hry8vjsvJyQFMnxINBkNdveTrKjtPQ51PmEi/Nzzpc+swGAy42UP/Lo14ukcwFzLziTmcwtrDyRxLvsqWE2lsOZGG/U9qRnZsxDM9mxAkk+duWk3f7waDwVTzazRiNBrLH9A2fJmKoii1XlKvLGaL2Ctsf/vtt4SHh+Pp6Wme+FaxrYuLC6GhoQB89913tGjRgq5du1b5e145zurObTQazaOTZW0q9q2Dg0ONX2N8fDx9+/bl2Wef5fXXX6/y+irauHEja9asIT093Tx5bf78+cTGxrJ06VKmTZtm0f7TTz+lffv2dOjQ4brHBejSpQvbt2//03bXUvb6y6hUqir7ykpSyvZV7t+K9yu+TysfR6PRWOxTqVSUlJRgNBprfMyKyp5nMBiwsbGxeKw2f0esngAfPnyYyMhICgsLcXJy4qeffiI8PJwDBw5gZ2dn/sUo4+vra176Izk52SL5LXu87LHrtcnJyaGgoMDia4Yyc+bMYebMmVX2r1+/3uKTT0O4XtG/qD/S7w1P+tw6KvZ7IDAhBFL9YH+6ir1X1KQUGFm++yLf7r5Ae0+Fvo2MBDpd+3iiZv7s/W5ra4ufnx+5ubnV1sbe6goLC1EUxTyAVCY317Qkn4eHB97e3gBV2hQXF1NUVGSxf/z48bz88svmSW7VKSoqori42Py8wMBAiouL+e2338yjwOfPnychIYEmTZqQk5NzzTirc+zYMYYNG8ajjz7K1KlT//Q5ZStelL3mivLz8y2en5uby8qVK3njjTdqFMvevXvx8vKqUdvKbG1tycvLs3iuk5MTSUlJZGdnm/t3z549GI1Gi0HAAwcOkJKSYs6dNm/ejJOTE66uruTk5FT5tytLYK9evWo+V0lJCXq9npycHIKCgvjmm29IS0vD3t4egN9//x2gSoxlioqKKCgoYOvWrRQXF1s8lp+fX/N+qHHLehIWFsaBAwfIzs7m+++/Z8yYMWzZssWqMb322mtMmTLFvJ2Tk0NgYCBRUVEWS5DUJ4PBQGxsLP379zcX6ov6J/3e8KTPrePP+v0pTCM5u85m8um2s2w9mc7+dBX709X0aOrBs38JoWdTD7nqXC3V9P1eWFjIhQsXcHJysvh6+Hah1WpRqVRV/maWrQTh6Oh4zb+ntra22NnZWTz+wgsv8MEHHxAbG1vtBDEwlTLY2tqan9ehQweGDh3KlClTWLBgAWq1mtmzZ9O4cWMeffRRNBrNNeOsrKzsISoqildffdWcaNnY2JgT+d27d/PUU08RGxtL48aN6du3L+7u7rzwwgu88cYb5hKI8+fPM2LECItzrly5kuLiYsaNG1cllnnz5tGkSRMiIiIoLCzks88+Y+vWraxbt+6GcpKQkBB2797N1atXsbe3x8vLi/vuu49XXnmFxYsXM3LkSH799Vc2btyIi4uL+RwajQaDwcCUKVOYPn06586d47333mPixInmwcrK/3ZlI+/Ozs7m/ytsbGywt7fHxcWFsWPHMnv2bF555RWmTZtGYmIiCxYsAEzvlepeX2FhIQ4ODvTq1avK70ZtPhBYPQG2s7OjWbNmAHTq1Ik9e/Ywb948HnnkEYqKisjKyrIYBU5JSTEXbvv5+bF7926L46WkpJgfK/tZtq9iGxcXl2pHfwHs7e3Nn0Qq0mg0Df4H2hrnFNLv1iB9bh1/1u/3hPlyT5gv8Zdz+GTraX45lMSO0xnsOJ1BRCMXnuvdlEGt/bC1kVU1a+PP+r3ierQ3styVtZXFXDn2ivuv97oqr8Xr5eXF6NGjefvtt3nwwQerfW5ZglXxsaVLl/Liiy8ybNgwioqKuOeee4iJiTH/jb9WnJX9+OOPpKWlsWzZMpYtW2beHxwcbF7JqrCwkISEBEpKSiwmvE2fPp1+/fphMBiIiIjg559/pkOHDhbH/+KLLxgxYkS1q0oYDAZeeeUVLl26hE6no23btmzYsIF77733ujFfy6xZs3juuedo3rw5er0eRVGIiIhgwYIFvPvuu7zzzjuMHDmSv//973zyySfmvlGpVPTt25cWLVrQp08f9Ho9jz32GDNnzrTov+rWUa68r2zbzc2NX375hejoaDp27EibNm148803GTVqFDqdrtp/F7VajUqlqvZ3qFZ/Q5RbzL333quMGTNGycrKUjQajfL999+bHzt+/LgCKHFxcYqiKEpMTIyiVquVlJQUc5vFixcrLi4uSmFhoaIoijJ16lSldevWFud47LHHlAEDBtQ4puzsbAVQsrOzb+al1UpRUZGyatUqpaioqMHOKaTfrUH63DputN8T0/OUf/x8RGk5439K8LQ1SvC0Ncpf3tuofLnjrJKvL66naO8cNe33goICJT4+XikoKGigyO5sJSUlSmZmplJSUmLtUO4qN9Lv33zzjaLRaJT8/PxqH7/e70Zt8jWrjgC/9tprDBw4kKCgIK5evcry5cvZvHkzv/76K66urjzzzDNMmTIFDw8PXFxcmDRpEpGRkXTv3h2AqKgowsPDefLJJ3n//fdJTk5mxowZTJw40fzpbsKECcyfP5+pU6cyduxYfvvtN1asWHHdpUuEEEJUL9BDx1tDI3ixb3O+ijvPl3HnuJBRwJs/H+XfG04yJrIJoyODZRk1IUSNfPXVV4SGhtK4cWMOHjzItGnTePjhh6/5LX1dsWoCnJqayujRo83X7G7bti2//vor/fv3B2Du3Lmo1WpGjhxpcSGMMjY2NqxZs4bo6GgiIyNxdHRkzJgxvP322+Y2ISEhrF27lsmTJzNv3jwCAgJYsmSJLIEmhBA3wd3Rjhf7NWd8r1BW7r3AJ1vPcDGzgLkbTrBoy2ke6RLIuHtCCHCXlSOEENeWnJzMm2++SXJyMv7+/jz00EPXvbBGXbFqAvzZZ59d93GtVsvHH3/Mxx9/fM02wcHBxMTEXPc4ffr0Yf/+/TcUoxBCiGtzsLNhdGQTRnUNIuZIMos2nyY+KYelO87x9c7zDGnrz/heTQlv1DATiIUQt5epU6cyderUBj+v1SfBCSGEuP3Z2qgZ2q4RQ9r6s+3UFRZvOcO2U1dYdeAyqw5cpncLb57rHUpkqKesHCGEsDpJgIUQQtQZlUrFPc29uae5N4cvZrN462liDieZL6zRLsCV53o3ZUCEHzZqSYT/jFLLC1AIcaerq9+J229tFSGEELeFNgGuzB/VkU1/78OT3YOxt1Vz8GI2f1u2j74fbmbZrvMUGkqsHeYtqWw5p9os7C/E3aDswjCVrwJXW7UeAdbr9ezatYvz58+Tn5+Pt7c3HTp0ICQk5KYCEUIIcWcK9nRk1vDWvNivOV/tOMeXcec5l57P9J+OMDf2BE/3DOGJbsG46mQd6DI2Nja4ubmRmpoKgE6nk9KRm2A0GikqKqKwsPC2XFf5dlXX/W40GklLS0On02Fre3NFDDV+9vbt25k3bx6//PILBoMBV1dXHBwcyMjIQK/XExoayvjx45kwYQLOzs43FZQQQog7j5eTPVOiwniud1P+u+cCS34/w+XsQv71awILNp3isa5BjP1LCI3c6nf5o9tF2QWdypJgceMURaGgoAAHBwf5INGA6qPf1Wo1QUFBN328GiXAQ4cOZd++fYwaNYr169fTuXNni/XZzpw5w++//863337LRx99xFdffWVeykwIIYSoyNHelrF/CeHJyGDWHLrM4i1nOJ58lSXbzrJ0xzmGtW/Mc71DaeF7dw+mqFQq/P398fHxwWAwWDuc25rBYGDr1q306tVLrjjZgOqj3+3s7OpkNLlGCfDgwYP54Ycfrhl8aGgooaGhjBkzhvj4eJKSkm46MCGEEHc2jY2aBzoEMLx9YzafSGPR5tPsOpvBD/su8sO+i/Rt6cOEPk3pHOx+V4/a2djY3HS9493OxsaG4uJitFqtJMAN6Fbu9xolwM8991yNDxgeHk54ePgNBySEEOLuolKpuDfMh3vDfNifmMniLWf4NT6ZjcdT2Xg8lY5Bbkzo3ZR+rXxRy8oRQog6IJXgQgghbhkdgtxZ9GQnNk7pzWNdA7GzUbMvMYvxX++l/9wtrNhzAX2xrBwhhLg5tU6AS0pK+OCDD+jatSt+fn54eHhY3IQQQoibFertxJwRbdn26r38rU9TnLW2nE7LY+oPh+j1/iYWbzlNTqHUxQohbkytE+CZM2fy0Ucf8cgjj5Cdnc2UKVMYMWIEarWat956qx5CFEIIcbfycdYy9b6W7Hj1r0wf1Ao/Fy0pOXrm/O84Pef8xpz/HSM1p9DaYQohbjO1ToCXLVvGp59+yssvv4ytrS2PPfYYS5Ys4c0332Tnzp31EaMQQoi7nLNWw7O9Qtk69V7ef7AtzXycuKovZvGWM/zlvU1M+/4Qp9NyrR2mEOI2UesEODk5mTZt2gDg5OREdnY2APfffz9r166t2+iEEEKICuxs1TzcOZD1L/Xi09Gd6RzsTlGJkf/+cYF+H21h/Fd/sC8x09phCiFucbVOgAMCAszLnDVt2pT169cDsGfPHuzt7es2OiGEEKIaarWK/uG+fB/dg+8nRNKvlS+KAuvjUxixYAcPL4rjt+MpGI2KtUMVQtyCan0duQceeICNGzfSrVs3Jk2axBNPPMFnn31GYmIikydPro8YhRBCiGvq3MSDJU08OJlylU+2nmHVgUvsPpfB7qUZtPB14rleTRnSrhF2trLwkRDCpNYJ8D//+U/z/UceeYSgoCDi4uJo3rw5Q4YMqdPghBBCiJpq7uvMvx5qx5SoFnyx/RzLdyVyIiWXl1ce5IP1CTzzlxAe7RqEk32t//QJIe4wN/2/QGRkJJGRkXURixBCCHHT/F0deH1QKybe24xlu87z+bZzJGUX8s7aY/xn40lGRzZhTI8meDtL2Z4Qd6saJcCrV69m4MCBaDQaVq9efd22Q4cOrZPAhBBCiJvh6qDhb32aMbZnCD/tv8QnW89w9koe8zed4pPfz/BQpwCevSeUJl6O1g5VCNHAapQADx8+nOTkZHx8fBg+fPg126lUKkpK5Ao9Qgghbh1ajQ2PdQ3i4c6BxMYns3DLGQ5eyGLZrkSW705kYGs/JvRuStsAN2uHKoRoIDVKgI1GY7X3hRBCiNuFjVrFfa39GRDhx66zGSzecppNCWnEHE4m5nAykaGeTOjTlF7NvVCpVNYOV4jbV0kxJB9EfeZ3up5ZBQWRoPGxdlQW6mQmQFZWFm5u8slZCCHErU+lUtE91JPuoZ4cT87hky1nWH3wMnFn0ok7k04rfxcm9A5lcBt/bG1k5Qgh/lSxHi7vh/Pb4dx2uLALinKxAfyB4gs7IeLWKpGtdQL83nvv0aRJEx555BEAHnroIX744Qf8/f2JiYmhXbt2dR6kEEIIUR9a+rnw0SPteXlAGJ/9fpbv9iRyLCmHF787wPvrEnj2nhAe7hKIzk5WjhDCrCgfLv1hSnbPb4eLe6C40iXJta4YA7sTn+dOmE+EdeK8jlr/Ri9atIhly5YBEBsby4YNG1i3bh0rVqzglVdeMV8YQwghhLhdNHZz4M0h4bzQtxlfx51n6Y5zXMoq4K1f4plXYeUID0c7a4cqRMPTX4XEXaZk9/wOuLQXjAbLNjovCO4BwT2hSU/wCaekxMjpmBjC3IKsE/d11DoBTk5OJjAwEIA1a9bw8MMPExUVRZMmTejWrVudByiEEEI0FDedHZP6NufZXqGs3HuRT7eeITEjn3kbT7J462ke6RzIuHtCCfTQWTtUIepPfgYk7ixNeLdD0kFQKs0Bc/YvT3aDe4JXC6hcO19y684bq3Vxk7u7OxcuXABg3bp19OvXDwBFUWq9AsScOXPo0qULzs7O5hUmEhISLNr06dMHlUplcZswYYJFm8TERAYPHoxOp8PHx4dXXnmF4uJiizabN2+mY8eO2Nvb06xZM5YuXVrLVy6EEOJuodXY8GT3YDb9vQ/zR3WgdWMXCg1Gvow7T58PNvPCt/s5ejnb2mEKUTdyU+HoKoh5BRb2hPdD4bvHIG6+qbZXMYJbMLR/HIZ9DC/shynH4MHPoPNY8A6rmvze4mo9AjxixAhGjRpF8+bNSU9PZ+DAgQDs37+fZs2a1epYW7ZsYeLEiXTp0oXi4mJef/11oqKiiI+Px9GxfF3GZ599lrffftu8rdOVf/IuKSlh8ODB+Pn5sWPHDpKSkhg9ejQajYZ3330XgLNnzzJ48GAmTJjAsmXL2LhxI+PGjcPf358BAwbUtguEEELcJWzUKu5v24jBbfzZcTqdRVtO8/vJK6w+eJnVBy9zT3MvJvRuSo+mnrJyhLh9ZF8ylTKc32b6eeVE1TaezctHd4N7gGtAw8dZj2qdAM+dO5eQkBASExN5//33cXJyAiApKYm//e1vtTrWunXrLLaXLl2Kj48Pe/fupVevXub9Op0OPz+/ao+xfv164uPj2bBhA76+vrRv355Zs2Yxbdo03nrrLezs7Fi0aBEhISF8+OGHALRq1Ypt27Yxd+5cSYCFEEL8KZVKRc9mXvRs5sWRS9l8svUMaw5d5veTV/j95BXaNHblud6hDGztj41aEmFxC1EUyDxXXr97bhtkna/azrd1aQ1vaR2v0621bFldq1UCnJOTw65du2jZsiWjR4/G29vb/NjkyZNvOpjsbNPXSR4eHhb7ly1bxjfffIOfnx9DhgzhjTfeMI8Cx8XF0aZNG3x9fc3tBwwYQHR0NEePHqVDhw7ExcWZSzUqtnnppZeqjUOv16PX683bOTk5ABgMBgwGQ7XPqWtl52mo8wkT6feGJ31uHdLvNy7MR8eHD7bmpb6hfLH9PCv3XeLwpWyeX76fJp4JvDm4Jfc096r2udLv1nFX9buiQPpJ1Ik7UCXuQJUYh+pqkmUTlRrFry1KUCRKUA+UwO7g4G55nDroq4bu99qcp8YJ8IEDBxg0aBApKSkoioKzszMrVqyosxFUo9HISy+9RM+ePWndurV5/6hRowgODqZRo0YcOnSIadOmkZCQwI8//giYJuVVTH4B83ZycvJ12+Tk5FBQUICDg4PFY3PmzGHmzJlVYly/fr1F+UVDiI2NbdDzCRPp94YnfW4d0u83p7MaWraD35PVbE1WcS49n7Ff7aO9p5EHgo242Vf/POl367gj+10x4lJwEc+843jlJuCZexz74qsWTYwqGzJ1oaQ7hZHu1JIMx+YU2zhAEXBKgVNx9RpiQ/V7fn5+jdvWOAGeNm0aISEh/PDDD2i1WmbNmsXzzz/PyZMnbyjIyiZOnMiRI0fYtm2bxf7x48eb77dp0wZ/f3/69u3L6dOnadq0aZ2cu7LXXnuNKVOmmLdzcnIIDAwkKioKFxeXejlnZQaDgdjYWPr3749Go2mQcwrpd2uQPrcO6fe69TCQqy/mP7+d5su48xxIV3PyqoYX+zbjyW6B5gtqSL9bxx3V78ZiVMmHykd3L+xEVWg5IVOx1aI07mQa3Q2KRGncGReNDhcgpAFDbeh+L/vGviZqnADv3buX9evX07FjRwA+//xzPDw8yMnJuemk8Pnnn2fNmjVs3bqVgIDrF1mXLbV26tQpmjZtip+fH7t377Zok5KSAmCuG/bz8zPvq9jGxcWlyugvgL29Pfb2VT+2azSaBv/FscY5hfS7NUifW4f0e91x12j4x9DWPNg5kBmrjrA/MYt3/5fAqgNJvPNAazoGlX/FLP1uHbdlvxfr4dK+8hre0qusWbBzgsBu5vpdVeOOqGyv8fWDFTRUv9fmHDVOgDMyMiySUzc3NxwdHUlPT7/hBFhRFCZNmsRPP/3E5s2bCQn5888lBw4cAMDf3x+AyMhIZs+eTWpqKj4+poLt2NhYXFxcCA8PN7eJiYmxOE5sbCyRkZE3FLcQQghxLRGNXPlhQg/++8cF/vm/48Qn5TBy4Q4e7RLElL71882luIMU5sCF3ZAYZ7pd2lvtVdYIKp2w1qQn+LUDG7laYW3Uqrfi4+NujuirAAAgAElEQVTNdbVgSmCPHTvG1avltSZt27at8fEmTpzI8uXL+fnnn3F2djYf29XVFQcHB06fPs3y5csZNGgQnp6eHDp0iMmTJ9OrVy/zeaKioggPD+fJJ5/k/fffJzk5mRkzZjBx4kTzKO6ECROYP38+U6dOZezYsfz222+sWLGCtWvX1ublCyGEEDWiVqt4rGsQUeG+zPnfcb7fe5Fvdyey7kgSg/xVDFQUa4cobhW5qaaR3cQ408+UI1UvOlHNVdZQ21gn3jtErRLgvn37olT6pb3//vtRqVQoioJKparVxTAWLlwImC52UdEXX3zBU089hZ2dHRs2bODf//43eXl5BAYGMnLkSGbMmGFua2Njw5o1a4iOjiYyMhJHR0fGjBljsW5wSEgIa9euZfLkycybN4+AgACWLFkiS6AJIYSoV55O9nzwUDse7hzIjFWHOZGSy7LTNiR8tod3R7Slha+ztUMUDUlRIOOM6SpriTvgfBxknK7azi3YlPAGRZp+eja77S40caurcQJ89uzZOj955WS6ssDAQLZs2fKnxwkODq5S4lBZnz592L9/f63iE0IIIepC1xAP1r5wD59sOcW8DSf443wWg+b9zjP3hPBi3+bo7OTr6zuSsQRSjpaP7ibuhNzkSo1UphHd4MjyhNelkVXCvZvU+DcuODi4PuMQQggh7mgaGzXj7wlBd+UY2/P92XA8jcVbzrDmYBL/GBJOVET1F3wStxFDIVzeV5rwxpkmrOkrrUyg1kDjjuXJbmDXqmvwinpXowQ4MTGRoKCgGh/00qVLNG7c+IaDEkIIIe5UHvaw8IEObDmZwT9WH+VSVgHjv95Lv1Y+/GNIBIEeDbvevLgJhdmmCWtlNbyX9kGJ3rKNnZMpyQ3qYRrlbdwJNFVXoBINq0YJcJcuXRg+fDjjxo2jS5cu1bbJzs5mxYoVzJs3j/Hjx/PCCy/UaaBCCCHEnaRfuC89m3nxf7+d5JOtZ9hwLJVtp67wQt/mjPtLKHa2amuHKCq7mlye7CbGQfIRoFI5p6N3+ehuUKTpEsOyQsMtp0b/IvHx8cyePZv+/fuj1Wrp1KkTjRo1QqvVkpmZSXx8PEePHqVjx468//77DBo0qL7jFkIIIW57DnY2TL2vJQ90aMyMVUfYdTaD99cl8NO+S8wa3pruoZ7WDvHuVTZhreIKDZnVzIdyb1I+uhvUAzybyoS120CNEmBPT08++ugjZs+ezdq1a9m2bRvnz5+noKAALy8vHn/8cQYMGGBxCWMhhBBC1ExzX2e+G9+dn/ZfYvbaY5xMzeXRT3YyomNjXh/UCi+nW+eiBncsYwkkH7acsJaXWqmRyjSiWzZhLSgSXPytEq64ObUak3dwcODBBx/kwQcfrK94hBBCiLuSSqViRMcA+rb05f1fj7N8dyI/7rvExmOpTL0vjMe6BKFWy8hinTEUmi4yUbYc2YXdUHTVso2NHTTqWD66G9gVHNysE6+oU7VKgM+dO0dsbCxFRUX06dOHiIiI+opLCCGEuCu56jTMfqAND3YKYMaqIxy9nMP0n46w4o+LzB7emtaNXa0d4m3JtjgP1cn1cKn0KmuX90NJkWUjO2cI6lZew9uoI2i01glY1KsaJ8CbNm3i/vvvp6CgwPREW1s+//xznnjiiXoLTgghhLhbdQhy5+eJPfl653k+XH+CgxeyGDp/G6Mjm/ByVAuctRprh3jrUhTISjQtQ5a4E9vEOAalHkN1uPKENZ/y0d3g0glrcoW1u0KNE+A33niD/v37s3DhQrRaLTNmzGDq1KmSAAshhBD1xNZGzdM9QxjUxp9Za+JZcyiJpTvOEXM4iTfuD+f+tv6oZMIVlBSbLiGcuBMu7ITEXXD1svnhsh5S3ENQBfcsr+H1CJUJa3epGifAR44cYceOHfj7m4q9//Wvf7F48WLS09Px9JRZqkIIIUR98XXRMn9URx7pksabPx/l7JU8Jn27nxV/XODtYa0J8XK0dogNS38VLu4xJboXdsLFP6Ao17KN2hb82kJQd4obd2FDwlX6DhuFRiMj56IWCXBOTg5eXl7mbZ1Oh4ODA9nZ2ZIACyGEEA3gnube/O/Fe1i85Qwfbz7F7yevMODfW4nu3ZToPk3Rau7Qr++zL5WP7CbGmUZ7FaNlG3sX0yS1wO6mOt7GncDO9MFAMRjQn4mxQuDiVlWrSXC//vorrq7lxfdGo5GNGzdy5MgR876hQ4fWXXRCCCGEsKDV2PBiv+YMa9+IN1cfZeuJNOZtPMnPBy7x9rDW9Grhbe0Qb46xBFKPmRLdC7tMSW92YtV2rkGlE9a6m5Jen1ZSvytqrFYJ8JgxY6rse+6558z3VSoVJSUlNx+VEEIIIa6riZcjXz7dhZjDyby95ijn0vMZ/fluBrf15837w/F1uU1WLyjKK12OrHR09+Ie0OdYtlGpTRPUgiJNSW9gd3BtbJ14xR2hxgmw0Wj880ZCCCGEaDAqlYrBbf3p1cKLubEnWbrjLGsPJbElIY0p/VswOjIYW5tb7JLKV1NKyxlKb8mHwFhs2cbOCQI6mxLewG6m+/bO1olX3JHk4tRCCCHEbc5Zq+HNIeGM7GS6pPL+xCzeXhPP93svMvuB1nQIcrdOYEYjXEkoXZ2hdIQ381zVds6NTKUMZTefCLCRFEXUnxq/u1avXl2jdlIDLIQQQlhHRCNXfpjQg+/2XOC9dceJT8phxMIdPNY1iGkDWuKqq+cVEAyFcHlf+ejuhV1QmFWpkQp8I0wju2UlDa6BshyZaFA1ToCHDx9usa1SqVAUpco+qQEWQgghrEetVjGqWxBREb7MiTnOD/susnxXIr8eSea1Qa0Y2bFx3a0dnHfFcu3dy/vBaLBsY+tQWs5QOlktsAto5Wp2wrpuuAbY2dmZgwcPEhoaWudBCSGEEOLmeDnZ8+HD7Xi4s+mSyidTc/n7yoOs+OMCs4e3prlvLWtqFQXST1VIeHeatitz8rUc3fVrCzay9q64tUiBjRBCCHEH6xbqScyL9/DZtrPM23CS3WczGDjvd8bdE8oLfZuhs7tGKqC/alqd4cIe08oMF/dAQUbVdt6tyldmCOoO7k2knEHc8iQBFkIIIe5wGhs1E3o35f62/sz8JZ7Y+BQWbTnNLwcv89bQCPq39DaN5l7cAxd3m5Le1HjAstQRG3vTBSaCSkd4A7qAzsMqr0mImyEJsBBCCHGXCHDX8enozmw6cIqf164m6OpRbL89SZ7mDI7Gq1Wf4BpkqtkN6AIBXcGvDdjaNXzgQtSxG06AVSpV3RXRCyGEEKJ+GI1w5YTF6O69ace5FwXKSnONUKhoyHSLwCf8HmyCupmSXmc/q4YuRH2pcQLs7u5ukfDm5ubSoUMH1GrLBbYzMqqpDxJCCCFEwyjIgkt/lNfuXvoDCrOrtnMLhsCupLq2Ye4xN1ZecqM4xZbmihPvNG9NN2fPho9diAZS4wT43//+d33GIYQQQojaMhoh7bhl7e6VhKrtbB2gcUfTqG5gV2jcGZx9AfAB3u2r0HnfJd6NOcbJ1Fwe+WQnIzsG8Pqglng62TfsaxKiAdQ4AR4zZkydn3zOnDn8+OOPHD9+HAcHB3r06MF7771HWFiYuU1hYSEvv/wy3333HXq9ngEDBrBgwQJ8fX3NbRITE4mOjmbTpk04OTkxZswY5syZg61t+cvbvHkzU6ZM4ejRowQGBjJjxgyeeuqpOn9NQgghRL3JzyhdmWF36ejuXtDnVG3nHlKe7AZ0MV144jpLkalUKkZ2CqBvKx/e/zWBb3cn8sO+i2w4lsK0+1ryaJdA1GopexR3jpueBHfmzBkKCgpo1apVlXKIP7NlyxYmTpxIly5dKC4u5vXXXycqKor4+HgcHR0BmDx5MmvXrmXlypW4urry/PPPM2LECLZv3w5ASUkJgwcPxs/Pjx07dpCUlMTo0aPRaDS8++67AJw9e5bBgwczYcIEli1bxsaNGxk3bhz+/v4MGDDgZrtACCGEqHvGEkg9Vr4E2YXdkH6yajuNzrQyQ0CX8puT9w2d0k1nx7sPtOGhTgFM/+kI8Uk5vP7TYVbuvcA7w1sT0UguYCHuDDVOgIuKipg9ezb79u2je/fuvPrqqzzxxBOsWLECgLCwMGJiYmjSpEmNT75u3TqL7aVLl+Lj48PevXvp1asX2dnZfPbZZyxfvpy//vWvAHzxxRe0atWKnTt30r17d9avX098fDwbNmzA19eX9u3bM2vWLKZNm8Zbb72FnZ0dixYtIiQkhA8//BCAVq1asW3bNubOnSsJsBBCiFtDfkZ5ontxD1zaB0XVrMzg0bR0dLd0ZQafcLCp20WdOgS5s/r5nny98zwfrj/B/sQshvzfNsb0aMKU/i1w1sqFLcTtrca/Ma+99hpff/01w4YN4/PPP2f37t0kJCSwfPly1Go1s2bNYvr06SxbtuyGg8nONhXpe3iY1hTcu3cvBoOBfv36mdu0bNmSoKAg4uLi6N69O3FxcbRp08aiJGLAgAFER0dz9OhROnToQFxcnMUxytq89NJL1cah1+vR6/Xm7Zwc09dLBoMBg8FQ7XPqWtl5Gup8wkT6veFJn1uH9Lt1mPtdXwDJh1Ff+gPVpT9QXdqDKuNMlfaKnSNKo44ojbugNO6E0rgz6CpNTjMqVS8/XEee6BpA/5ZezPnfCdYeSeaL7eeIOZTEBw+2oXvo7bP+r7zfraOh+70256lxAvz999+zdOlSBg0axIkTJ2jZsiVr165l4MCBAPj4+PD444/XPtpSRqORl156iZ49e9K6dWsAkpOTsbOzw83NzaKtr68vycnJ5jYVk9+yx8seu16bnJwcCgoKcHBwsHhszpw5zJw5s0qM69evR6fT3fBrvBGxsbENej5hIv3e8KTPrUP6vWFoizJwzz+DW/4ZeuSdxu7gs9ga9VXaXbX3J9OxKRmOzch0bEaONgBUasgHTpbAyV0NHzwQ5QxBrVSsPKsm5aqeMUv3MLKJkb/4KX/+5FuIvN+to6H6PT8/v8Zta5wAX758mXbt2gHQokUL7O3tadasmfnxFi1amBPOGzFx4kSOHDnCtm3bbvgYdeW1115jypQp5u2cnBwCAwOJiorCxcWlQWIwGAzExsbSv39/NBr5qqmhSL83POlz65B+r0eFOaiSDqC6vK/8llv176Ni52Qa1W3UGSWgM0qjTmh1HvgD/g0f9Z8aBPzNUML0VfGsPpTEyrM22PsE8vrAMDQ2tZsD1NDk/W4dDd3vZd/Y10SNE+CSkhKL4G1tbbGxsTFvq9VqFOXGPgk+//zzrFmzhq1btxIQEGDe7+fnR1FREVlZWRajwCkpKfj5+Znb7N692+J4KSkp5sfKfpbtq9jGxcWlyugvgL29Pfb2VZd90Wg0Df6LY41zCul3a5A+tw7p95tUrIeUI6Z63Ut7TbcrJ6q2U6nBJxyjf3sOpWuIuO9pNP6tUaltqra9hWk0GuY91oGWjVz4168JfLPrAmfT81kwqhOuulv/fSTvd+toqH6vzTlqVTX/66+/4upqmgFqNBrZuHEjR44cASArK6s2hwJAURQmTZrETz/9xObNmwkJCbF4vFOnTmg0GjZu3MjIkSMBSEhIIDExkcjISAAiIyOZPXs2qamp+Pj4AKahdhcXF8LDw81tYmJiLI4dGxtrPoYQQgjxp4xGyDhdnuhe2gvJh6GkqGpbtyDTygxlN/92YOdIicHA+ZgYInzC4TZLfsuoVCr+1qcZzbydeOm/B9h+Kp3hC7bz6ejONPNxsnZ4QtRIrRLgymsBP/fccxbbtb008sSJE1m+fDk///wzzs7O5hIKV1dXHBwccHV15ZlnnmHKlCl4eHjg4uLCpEmTiIyMpHv37gBERUURHh7Ok08+yfvvv09ycjIzZsxg4sSJ5lHcCRMmMH/+fKZOncrYsWP57bffWLFiBWvXrq1VvEIIIe4iV5Mtk91L+0FfzRXVHNwtk91GHW94GbLbSVSEHz9E92Dcl39w9koeDyzYzvxRHend4s5/7eL2V+ME2Gg01vnJFy5cCECfPn0s9n/xxRfmi1TMnTsXtVrNyJEjLS6EUcbGxoY1a9YQHR1NZGQkjo6OjBkzhrffftvcJiQkhLVr1zJ58mTmzZtHQEAAS5YskSXQhBBCmBTmQNKBCsnuPsi5VLWdrRb825cmux1NN/cQqOUA0J2ilb8LPz/fk+hv9rLnXCZPf7GbGYPDebpnk1oPignRkOp24cBaqknNsFar5eOPP+bjjz++Zpvg4OAqJQ6V9enTh/3799c6RiGEEHeY4iJIPVqe6F7aC2kJQKW/SSo1eLcqTXRLR3d9Wl33imp3Iy8ne74Z140ZPx1h5d6LvL0mnpOpV5k5tDV2trf25Dhx97JqAiyEEELUK0WBjDOWpQxJh6Ck6hJkuAZZJrv+7cBealprwt7WhvcfbEuYnzPvxhzj290XOJ2Wx6InOuHhaGft8ISoQhJgIYQQd47c1Ep1u/ugsJpJ2lo3y7rdxh3Byafh472DqFQqxt0TSlNvJ174dj+7z2Yw7ONtLBndhTA/Z2uHJ4QFSYCFEELcnvS5Vet2sy9UbWdjbxrNrZjseoTetXW79e3elj78+LcePPPlHyRm5DNiwXb+81gH+rby/fMnC9FAJAEWQghx69PnmtbbTTpoul3eD2nHQak8QVsF3i0rTFLrBD7hYCtfwzek5r7O/DyxJ9HL9rLzTAbjvvqDV+9ryfheoTI5TtwSJAEWQghxaynIMq2vm3TQNMKbdBCunKTKJDUAlwDLut1G7cFevm6/Fbg72vH1M934x+qjLN+VyJz/HedESi7vjmiNve3tuQay+HOFxYWk5qeSnJfMpZxLbC3cSteCrvhrbq3rG9Y6AXZ3d6/205tKpUKr1dKsWTOeeuopnn766ToJUAghxB0sL708yS27ZZ6tvq1zI1MpQ9mtcUdw9mvYeEWtaGzUzB7emjBfZ95eE88P+y5y9koui5/sjLdz1SuuiltbUUkRKfkppOSlkJyfTHKe6Wbel5dMpj6zyvMezH4Qf5fbPAF+8803mT17NgMHDqRr164A7N69m3Xr1jFx4kTOnj1LdHQ0xcXFPPvss3UesBBCiNvU1WTLRDfpYPU1u2C6kpo52e0A/m1lktptSqVSMaZHE0K9HZm4bB/7ErMYNn8bn47pTEQjV2uHJ0oZjAbS8tMsktqy+8n5yaTkpZBemF6jYznYOuCr88XHwQdDpgFX+1vv37nWCfC2bdt45513mDBhgsX+xYsXs379en744Qfatm3Lf/7zH0mAhRDibqQokH2xarKbm1x9e4+mpkS3UXvTT7+2oPNo2JhFvbunuTerJvZk3Jd/cOZKHg8ujGPuI+25r7WM4te3YmMxVwquWCSzlZPcKwVXUKorM6rE3sYeX50vfo5++Dn6VXvfxc4FlUqFwWAgJiaGMPewBniVtVPrBPjXX3/lvffeq7K/b9++vPzyywAMGjSIV1999eajE0IIcWtTFFPJQuVkN7+akSKVGrzCLMsY/NqA1qXh4xZWEertxE9/68nz3+7j95NXmPDNXv4e1YKJ9zaTyXE3qMRYQnph+nVHbtMK0jBWmTBalUatwVfni69jaVKrq5rkutm73RH/VrVOgD08PPjll1+YPHmyxf5ffvkFDw/TJ/a8vDycnWUSghBC3FGMJZB+2nJyWtIh0GdXbau2NV01zb+d6dLB/u3ANwLsHBs+bnFLcdVp+OKpLryz9hhLd5zjg/UnOJGSy/sPtkWrkclxFRkVIxmFGeYR27K624o1uGn5aRQrxX96LFuVLT46H1NC6+iLn86vPNEtTXI9tB6oVXfH1ftqnQC/8cYbREdHs2nTJnMN8J49e4iJiWHRokUAxMbG0rt377qNVAghRMMpKYYrCXC5wgS15MNgyKva1sbelNxWHNn1CQeNtuHjFrcFWxs1bw2NoIWvM2/+fITVBy9zPj2PT0Z3xtfl7njfGEoMpBakkpKXQmp+qmkiWelkspR8076aJrc2Khu8dd7lI7VlI7elia6fox8eWg9s1PIBo0ytE+Bnn32W8PBw5s+fz48//ghAWFgYW7ZsoUePHgDmUgghhBC3gWI9pMZbljCkHIXiwqptNTpT2YI52W0P3mFgo2n4uMVtb1S3IEK8HIletpeDF7MZOn8bn47uTNsAN2uHdlPyDHnmZNac3FZKdDMKM2p0LLVKjZfWy5zQVldz6+Xgha1aVratjRvqrZ49e9KzZ8+6jkUIIUR9y8+A1HjUlw/RPnEdtkv+ZbqghNFQta29i2lCWsUJap7NQEaRRB2KbOrJ6ol/4Zkv93AyNZeHFsXxwUPtGNKukbVDq0JRFDL1maZEtnSktnJym5qfSq4ht0bHq1hz66PzwU/nh4/Ox7ztq/OV5Lae3FCPGo1GTp06RWpqKkajZVF1r1696iQwIYQQN6HEAOmnTCO5KUdKfx6FnEsA2ADBFds7uFvW6/q3A/cQUN8d9YDCuoI8dfz4tx688O1+NiWkMenb/ZxMucpL/VqgVjfMhKuylRKqG7ktS3TT8tMoMhbV6HhOGifTUmClCW3ZfT9HP3Nye6dMKLsd1ToB3rlzJ6NGjeL8+fMoiuVyGSqVipKSkjoLTgghxJ9QFMhNtUxyU46a6ndLrvGH2i0Io3c4J3PsaPqXkdgGdgTXQJA/xMKKnLUalozpwnvrjvPJ1jP857dTnEzN5cOH26Gzu7kR0ILiAq6UXOGPlD+4or9SbVlCemF6jVZKAPDQephGbiuM3la+76iRCZ+3slq/oyZMmEDnzp1Zu3Yt/v7+8slFCCEaiqHQVK5gTnRLk978K9W3t3M2TU6rePNpBVpXSgwGjsfEENpyEGikflfcGmzUKl4f1IrmPk5M/+kI/zuSzPn0fJaM6UwjN4cq7YtKikgrSCMtP800aawgzTx5LLXA9DMtP42rhqumJ2y8/vltVbbmyWQVR24rbns7eGNnY1cPr140pFonwCdPnuT777+nWbNm9RGPEEKIsgtJVC5fSD8FSjXfsqnUpotJ+EaAb+vyZNctSEZ1xW3pgY7+uDnnM3XVNk5cPcrgL35jUAcdNpqrpBakmpPcLH1WjY+pQUMj50blSW3FkdvS7btpGbC7Xa0T4G7dunHq1ClJgIUQoi7or0LqMcvyhZSj1a+tC6ZaXd/Wlomud0uw0zVs3ELcgLJ1bdPy06odrS0bxU0vSDddlcwPHIBiYPX56o+pUWvw0fng7eCNt87bfN9H52PadvDBTePG1titDB48GI184yG4gQR40qRJvPzyyyQnJ9OmTZsqb6S2bdvWWXBCCHHHMJZA5rlKtbpHTPuqo9aYlhfzCbcc2XX2k1FdcctRFIWcohxzQpuSn2KR4JbdTy9Ir9G6tmBa29bLwQtPrTdJGXakZNihFLvQu2kzRndtg6+jDz4OPrjau/5pOabBYJCSTWGh1gnwyJEjARg7dqx5n0qlQlEUmQQnhBBgXmrMooQh9RgY8qtv7+xfoU63NNH1bA62UmcorKsssU3LT+NK4RVzMltdzW1NV0dQocJD62EeofV2MNXcVhy99dZ5427vbr5wg9Go8GFsAh9vOk1sOihX7fn3o6E42cvyYOLG1Pqdc/bs2fqIQwghbj/FRaa63NT4apcaq8JWa5qEVjHR9YkAR8+GjVvc9QwlBtIL002JbcEVc9lBWoFpu+LNUN0a0dfgZu9mLjsoS24rliJ467zxdPBEo65dGYJareKVAS1p4evMK98fYsOxVEYu2MGSMZ0J9JDyH1F7tU6Ag4OD/7yREELcSQoy4cpJuHLCdEsr/Zl5rvpJaWCagFaxTte3NXiEykUkRL1RFIWrhqumxDX/ynUT29pMHgNwsXPB28EbLwev8oS2Uq2tl4MX9jb29fTqTIa1b0ywpyPPfvUHCSlXGfbxdhY90YmuIR71el5x56lRArx69WoGDhyIRqNh9erV1207dOjQOglMCCEalNEIORfLk9srJ0qT3gTIS7v28yyWGgs3JbqlS40JUReKjcWkF6RzpdAysa08Unul4Ar6En2Nj2urssXTwdOc2HrpvPBy8MLbwdtyv4PXLbXsV/tAN1Y/35Nnv/qDI5dyeHzJTt4Z3ppHugRZOzRxG6lRAjx8+HCSk5Px8fFh+PDh12wnNcBCiFueoQDST1dIcstup6C44NrPc2kMXs3Bq4XlTSaliRuUZ8gzlyCU3apLbDMLM00rItSQs8bZlMDqvPHSXjuxdbV3vW2X/PJ3dWDlcz34+8qDrD2cxLQfDnMiJZfXB7XCpoGuHCdubzVKgCte7rjypY9vxtatW/nXv/7F3r17SUpK4qeffrJIsJ966im+/PJLi+cMGDCAdevWmbczMjKYNGkSv/zyC2q1mpEjRzJv3jycnJzMbQ4dOsTEiRPZs2cP3t7eTJo0ialTp9bZ6xBC3ILyrlQayT0BaQmQlQjXSibUGvBsZpnoercw7bN3btDwxe3HqBjJ0eeQXphORmGG6WdBhsX99IJ0LuRcYPaK2RRc7wNXJTYqGzy1nuWJbenIbFliW3bf08ETB9uqF4y4EznY2TB/VAdabHRm7oYTfLbtLKdSc/m/UR1w0cpSZ+L6al0DXFhYiFarrZOT5+Xl0a5dO8aOHcuIESOqbXPffffxxRdfmLft7S3rix5//HGSkpKIjY3FYDDw9NNPM378eJYvXw5ATk4OUVFR9OvXj0WLFnH48GHGjh2Lm5sb48ePr5PXIYSwEmMJZJ2vpmzhBBRkXPt5WlfwCitPcMuSXbdgsJFZ5aJcYXEhGYUZ5lt6Qbo5wS3bLrufWZhJybVqwisrHUvS2epME8O0109s3ezdzCsiiHIqlYoX+zWnua8TU1YcYMuJNB74eDufjelCEy+5FLG4tlr/T+/m5kbXrl3p3bs3ffr0oUePHjg43NinzYEDBzJw4MDrtjwtFD0AACAASURBVLG3t8fPz6/ax44dO8a6devYs2cPnTt3BuD//u//GDRoEB988AGNGjVi2bJlFBUV8fnnn2NnZ0dERAQHDhzgo48+kgRYiNtFUV5pYls2ES3BdD/9FJRcZ+klt6AK5QrNy5NeRy8pW7hLGRUjWfos88hs2ehsxUS2YnKbX3yNpeuuw8XOBQ+tBx5aDzwdPE0/taafrnauJOxP4P5778ff2R+dRlYwqAuD2vgT5KFj3Jd/cDotj2Efb2fh4x3p0czL2qGJW1StE+ANGzawdetWNm/ezNy5cykuLqZz587mhLh///51GuDmzZvx8fHB3d2dv/71r7zzzjt4epqWDIqLi8PNzc2c/AL069cPtVrNrl27eOCBB4iLi6NXr17Y2ZUX8A8YMID33nuPzMxM3N3dq5xTr9ej15dPJMjJyQFMC2kbDDVfDuZmlJ2noc4nTKTfG565z4uK4GoyqvSTqNJNya0q/SSqKydQXWtZMUCx1YJHUxSv5iie5Tc8m8K1kovimi3Efye7k97rBcUFZBZmmpPZTH1mlWQ2Q28aoc3UZ2JUalfKp1Fr8NR64q51x8PelNi6a92r7PPUeuJm74bG5tpfvxsMBvS2evy1/mjQ3BH9f6sI89Hxw4Ru/G35AQ5ezObJz3cza2g4D3VqfEe93291SkkJSkEBxvx8irKzsb94EX1WFri51fu5a/Pvq1IUpeaV9ZUUFxezZ88eFi9ezLJlyzAajTc8CU6lUlWpAf7uu+/Q6XSEhIRw+vRpXn/9dZycnIiLi8PGxoZ3332XL7/8koSEBItj+fj4MHPmTKKjo4mKiiIkJITFixebH4+PjyciIoL4+HhatWpVJZa33nqLmTNnVtm/fPlydDr5tC7EjVIpJWiLMnAsSkNXlIZOn4ZjUSo6fRrO+iQ0JdcebdPbOnPVvhG5Wn+uahuRa+9PrrYR+XaecJtO5BFVGRUjBUoB+Uq++ZZnzCu/r+SRbzT9zFPyyDPmUUTNLsBQkYPKASeVE44qR5zUpp+OakecVE6m/WpH82P22MtVxG4jBiN8e1rN3itqVCiMb2kk3P2GU507m9GIymBArdejLioy/Sy9r9KXbheVPWbaVhXpTfeLyh9XVdyuJgm98Nx4CkJD6/3l5OfnM2rUKLKzs3Fxcblu2xsqdjtx4gSbN2823/R6Pffffz99+vS5kcNd06OPPmq+36ZNG9q2bUvTpk3ZvHkzffv2rdNzVfTaa68xZcoU83ZOTg6BgYFERUX9aYfWFYPBQGxsLP3795frljcg6febpCiQfwVVViJknUOVlYgq6zxknTfty76I6jo1kopKDW7BplFcr7KRXNNPtc4DV0AWF6sbDfFeNypGcg25ZBVmkanPJEufRXZRNln6rGvesvXZtVrxoIyd2s5cdlA2Quth71E+SlvhMTd7t1pfiKGuyP8xDWOoojD953hW7r3EN2ftWN6nE+cO7rit+10xGlEKCzHm52PMz0fJyyu/n1+AMb/idj7G/AKMpW2U/HyMBfkY88oeK21XUPOJmLWmVqPS6ShSq+ncqRPOkZH1d65SZd/Y10StE+DGjRtTUFBAnz596NOnD9OmTaNt27YN8uk4NDQULy8vTp06Rd++ffHz8yM1NdWiTXFxMRkZGea6YT8/P1JSUizalG1fq7bY3t6+ymQ7AI1G0+C/ONY4p5B+vy59rmniWeb50p/nKtw/D4a86z/fxs5Um+sWDO5NKHEJYO+ZdDr0fwSNTwvQaJGxtoZT0/e6oijkGfJMiWyFhDar0JS4Wuwv/Zmtz675pLBKnDXOuGndcLd3x03rhpt91ftl9bUeWg8cNY631Sit/B9T/2Y/0JbzGQXsPpvBxP8eJrppw/S7UlKCsaAQY36euRTAWFCAMa80CS1NPI1lSWp+pf15pe3zy38qpfe58S/tr0+tRq3TmW6OjuX3y7YdTfdV1bYpe7y8ndrREZWdHcXFxcTExNAqMrJB3u+1OUetE2Bvb2+OHz9OcnIyycnJpKSkUFBQ0CClARcvXiQ9PR1/f38AIiMjycrKYu/evXTq1AmA3377DaPRSLdu3cxtpk+fjsFgMHdMbGwsYWFh1db/CnHXKzFA9sVqktvS+/lX/uQAKnBpVJrgmpJci/tOfqAuL1kwGgwkZcbQwacVSELQIBRFIdeQS6Yxk/iMeHKLc6skrpmFmVUS22LjjdVO62x1uGvd+f/27jw8iipfH/hbvaY7KyFk0xC2sATZlxgBAQmERUAH70UIGtCBi5IBxSuK40VgroPjzKjgg+hchaiDMOLIIiKQH0vYA4mEJSCyR5EkbCEJ2Xo5vz86XaSzmWC6q5N+P8/TT1VXna46/YWQl9NVpwP0AXdDrT5A3ibvq1j31/srNkJLzYdOo8KHU/pg/PJ9+OlmCVaeUeMxs1X+Z0aYTHeDZkUQFRVB1FotiFYaVS2ue7soLXXuG5Ok6gHVaITk/SvhtIZAK4dVvedd5tPgAJyZmYn8/Hzs2bMHqampeO2113Dq1Cn07NkTQ4cOxZtvvlnvYxUVFeHcuXPy84sXLyIzMxOBgYEIDAzEokWLMGHCBISGhuL8+fOYN28eOnTogPj4eABAly5dMHLkSEyfPh0ffvghTCYTkpKS8OSTTyI8PBwAMHnyZCxatAjPPvssXnnlFZw8eRJLly7Fu+++29C3TtQ8CAEU5d0dsb11Cci/VLF+GSi4UvvX+9p5BdQcbgPaAAERgMa5X4dKthBbYi5BQXkBbpfdRkF5ge1RVlDrtsrr8sjs1rrPU5VBY5DDqkOgrbqsFGzd6VvEqOmQP/IvKbEFy4qltbgE1tKK58UV+0rvrltLS2yXBFS0/0dBEc5nX4fWVIZTm96CH0wQxSUQzr4hriKoSkaDLWgaKgKnoeK50WAbUa283du2dNhuNFTsqwi6BoPHhVVnuKdrgAMCAjBu3DgMGDAADz30EDZu3Ig1a9YgLS2tQQE4PT0dQ4cOlZ/br7tNTEzEihUrcPz4cXz66afIz89HeHg4RowYgT/96U8OlyesXr0aSUlJGDZsmPxFGMuWLZP3+/v7Y/v27Zg1axb69OmDoKAgLFiwgFOgUfNWVlgp3F52XM/PBky/MrWTxsvhMgW0iLwbdAMiAYPz7+b1FKXmUjmY3i6/7RhWKwfZGoLtvY7I2qmhRkuD7RpZe3D11/vfHZmtFGjtI7Oe8iUL9OuEEHcDanFFCK1h3VpSXHHtag1htaQYoqSGkNvII6ntK61XmwNEo3EMphVLW3D1dgis9gAqB1rvSu0NFe3t7TxwVLUpaXAA/vrrr+Wb306dOoXAwEAMHDgQf//73zF48OAGHWvIkCGoaxKKbdu2/eoxAgMD5S+9qE337t2xd+/eBvWNyC0JAZTeBgpzgKIcoDC3YpkDFF69G3Tr+hIIALbLFO6rEm4rrfuEOFymQHUrt5RXG2mtGlxrC7Pl1obPYFCZRtLAT+8HP53f3WXFw1/v77Bdfq7zg0FlwM5tOzFmzBhei9rMCIvFFjhLS+WlvF5SClFWZVlaAmtpmby0lpZA2JclpbCWlTouK4VVV5G8vGwjowYvW/A0GKo9d9znZQukBltwtWq1+MfO40i5bkC5RodFT/bDoG4RtqCq4ycUnqjBAXjmzJl4+OGHMWPGDAwePBjdunVzRr+IPIsQQPHNu2G2KNcWaB0CbsV2cz1HRQyBNYfbFm0A/whAw3/0AcBkMaHQVIii8iJ5WVRehCKT7VFYXig/LywvtG2v3NZU1KCvtK2JSlI5BNeaAquf3g/+On+HkGsfkb2XUSaTycTRKReyh1LLnTvQ5Oej/NIlWMxmh5BaW0B1CKQOy1LbiGlZmcPS6R/t10DS6ytCqEEOp1Wf1xpWjYaKgGu8u26sFHK9vCD9xv+Qm0wmdCwswnVTJL7MuIKk//cLvu7YBh0D+O+gp2pwAK466wIR1cFqtd009muhtii37m80q8rL33YzmW/FwyfEtqx8mYKXa6bsU1KZpUwOqHdMd+4G2VqCak1htsxS9usnqgcJEnx0PvUafa0aZr213lBxLmOnE0IAJpMtKFY87OvW0lKIsnJb6Cwrc1wvLYMoL7ONkpY5rlvLKl5XWgpreZnjeundc1T+8pV2ALJd9J4lvR4qLy9bqKy8NBig0usrLb2g0nvZll4GSF56h6XK4AVJ7wWVlx6SodJ1qfaAqnb/r2mWJOCNR7vg8s0SpF28iWc/PYINzw9ASx/es+CJ7ukaYIvFgg0bNuD06dMAgOjoaIwfPx7qJvADQNQoLGbgzrXqQdYh4FYE24ZMA2UIBHzDAN+QioAbYntuD7j2pbZpX4dpsphQbC5GsakYBaUF+Nn8Mw5dPYQSa0n1kdY6wqzJ2ngjXQaNAb5aX/jofOCj87m7rvWBr84XPlof+Xnl/b5aX/jp/eCj9YFaxX8D6yIH0PLyiiBZXhEQy23r5bZtcgCt2GaV21a8zlSpTQ1h0xZuS23HLSuraGNbh7Vh3wLnlDqo1VAbjbUE00pBtOqyciD10kOqvLQHVEOlY+n1v3nktLmxzwzx2Af7cflGMWb+MwP//H0M9Br+7HqaBgfgc+fOYfTo0bhy5Qo6deoEAFiyZAkiIiLw7bffon379r9yBCI3ZjHBq/wGpCsZQMn1u0G28GpFwK0Iu8XXgXp/naoEeLeqFGqrjNraA65PiNtdlmAVVpSYS1BsKpYDa7G5uMZtxSbbdod9NewvNhfXfPPWrnvvp7fWu1pQrW+Y9dX5wlvrDY3qnsYDmgRhtUKYTLYQWbE0FZdAl5uHsh9+gNli+W0h1B5ky8sgyk2O4bb87n5R1jij7Y1F0uttYVGns41i6nW2sKnXO6yrvPSQdBVt9TrH9cpt9LZ28rpebxtd9fKCpNNBpdfDrFLhu23bMHr0aF57rZAW3jp8ktgXjy8/gCOXbuH19Sfx9hOu+T4Dch8N/hd/9uzZaN++PQ4dOoTAwEAAwI0bNzBlyhTMnj0b3377baN3ksglUhZAu38p4gEgqx7tJTXgE1wRZkNrD7jewYDaueFKCIEyS5kcMGsLqpWf1xhiqwTZ33pt66/RqXQwao1AOdDKvxV8db5yIK0pzNa0zV0uHxAWi0PArLasWLdW22eCMJVXLGt5bX2WFcewmiof17a/8sfvlbUB8JNLq+RI0mrloCjpdLYgWrFuC486SNrK22whUt7mVREwdZXW9RVB1svLtt2+bg+j9kCq1SoSeCQFrs+l6joE++L9yb3wTPIRrMv4GR1DfDH9Yed/VS+5jwb/Vk5NTXUIvwDQsmVLvPXWWxgwYECjdo7IpfS+AACrpIbkGwbJIcjWcFmCsSVQ5SNvi9WCMksZyi3lKLWU2pYFF2xLc6nD9jJLWfWHuYZtteyreixnUkkqGDVG20NrhEFjuLus2FbT0qGdfV+lY2hUGphMJmzZsgWjRo2CVpIgzGZbcDObIUy2dZgrnhfatxdBmPIhzCbcMZkAs/nu60xmCLOp4nXVjyXMVfdXbmOCMFdsL7e3reF1Dscy20KmG3y0Xm9aLSSNBmYAOl9fh+BZZwjV6yHptBWhUycHTPvopqSrElTrOK6k1fLjeVLUkE7BeH1MNBZvPoU/f3ca7Vp5Y1iXEKW7RS7S4ACs1+tRWFhYbXtRURF0nEqEmrAjkX2RPnoBsi5cQOu2kSgX5ZVC5hWU3jyP8mvldYbUe56XVQhIAlAJQGWtsqxYV1fZrhWAvso2tRUwQAejSg+DpIMBOhhUtqWXpIMBWuihhZekhV5ooYMaeqihE2rooIFWqKATKmiEGlohQSNU0FglqCwCsFggLGbAbLGFPosFsJghzCUQlsKKEGqxba/YL8zmija27WazCQVmC25XaRNlMuH8K6827h+owiSdzhbyGrzU1rhdVdfrGnIOjQaSSiX/x4MfxZMnmzagDc7mFWHN4WzMXnMUXz8/AJ1CfZXuFrlAgwPwo48+ihkzZuCTTz5B//79AQBpaWmYOXMmxo0b1+gdJHKV89+uh3rH/0PPKsFTJQCpcgAVotaQ6hBGhXR3aQXUAlBZJYfXS1YBySqgatSvdy+peNw7AaC84uEKtX4QrVbbgptGIy+hta87bpc0Gkg6LaDR2EYs7du0WkhaTcX2Kq/TVjpu5f21bq/YV7k/GltorRxQodHwekKiJkCSJCwe3xUXrxfh0IWKmSFmDUAQZ4Zo9hocgJctW4bExETExsbKowZmsxnjxo3D0qVLG72DRK7S7poE36zGTKKiyvI3kCRbqFKpbKGwtqVGY5uOSKOGpK5Y12rurmvUtiBXpY2k1QDqKq/VaCBp1PL2ym3k7ZXbaNQVr9fc7YdDm8r9u9vGLAR2pe7BI/EjoDMY5HApv18iIifSqlVYkVBpZojPM7B6OmeGaO4aHIADAgKwceNGnD17Fj/88AMAoEuXLujQoUOjd47IlR4Ym4ii+7rj9JkfEP1AN2h0WkClhqRW2ZYatePzupaVQilUKltoVKtrDK32/XeX1Y/RnEcTJZMJ5gB/aFq2hJofxRORAmwzQ/TD4x/sR/rlW/jj+pP4K2eGaNbu+db0qKgoREVFNWZfiBRl7N0b2m7dkL9lCwJ4XSQRkUfpEOyD5ZN7Y+qqw/gq42dEBfvgvwZzatfmql4BeO7cufU+4DvvvHPPnSEiIiJSysMdW2HBo9FY+M0pvLX1B7Rv5YO4aM4M0RzVKwAfPXq0XgfjRwVERETUlCU+ZJsZYnVaNuasPYp/P/8QOoc2/6+W9zT1CsC7dv2Gr2giIiIiaiIkScLCcV1x8fodHDh/A88mp2NjEmeGaG7qfYv1hQsXbN/jTkRERNSMadUqfJDQG21aGnElvwT/9XkGyswWpbtFjajeATgqKgrXrl2Tn0+cOBG5ublO6RQRERGRkgKMOnyc2A++XhpkXL6F+V+f4EBgM1LvAFz1D33Lli24c+dOo3eIiIiIyB10CPbBBwm9oVZJ+Pr7K/hozwWlu0SNhLPMExEREdViUFQrvDE2GgDwl60/IOUUP/1uDuodgCVJqjbLA2d9ICIioubu6dg2mPJgawgBzFl7FKevFijdJfqN6v1FGEIITJ06FXq97S7I0tJSzJw5E97e3g7tvv7668btIREREZHC3hhrmxli/7kb+P2n6dgwawBa+XJmiKaq3iPAiYmJCA4Ohr+/P/z9/TFlyhSEh4fLz+0PIiIiouZGq1bhg8l90DbIu2JmiHSUmjgzRFNV7xHgVatWObMfRERERG7N36jFx4l98fjy/fg+Ox+vfX0Cf//PHrwktAniTXBERERE9dS+lQ8+SOhjmxni6BWsSD2vdJfoHjAAExERETXAwKggLKyYGeKv285gW1aOwj2ihmIAJiIiImqgp2Lb4OnYSAgBvPivTJz6hTNDNCWKBuA9e/Zg7NixCA8PhyRJ2LBhg8N+IQQWLFiAsLAwGAwGxMXF4ezZsw5tbt68iYSEBPj5+SEgIADPPvssioqKHNocP34cgwYNgpeXFyIiIvD22287/b0RERFR87bg0WgM7BCE4nILfv/pEeQVlirdJaonRQPwnTt30KNHDyxfvrzG/W+//TaWLVuGDz/8EGlpafD29kZ8fDxKS+/+BUtISEBWVhZSUlKwefNm7NmzBzNmzJD3FxQUYMSIEYiMjERGRgb++te/YuHChfjHP/7h9PdHREREzZdGrcLyyb3RLsgbv9wuxX99nsGZIZqIes8C4QyjRo3CqFGjatwnhMB7772H119/HePHjwcAfPbZZwgJCcGGDRvw5JNP4vTp09i6dSuOHDmCvn37AgDef/99jB49Gn/7298QHh6O1atXo7y8HCtXroROp0PXrl2RmZmJd955xyEoV1ZWVoaysjL5eUGB7WMNk8kEk8nUmCWolf08rjof2bDurseaK4N1Vwbrrgxn1t2oBT6a0hNPfJSGo9n5mLfuGP72xAOcGQKu//vekPNIQgjhxL7UmyRJWL9+PR577DEAwIULF9C+fXscPXoUPXv2lNsNHjwYPXv2xNKlS7Fy5Uq89NJLuHXrlrzfbDbDy8sL69atw+OPP46nn34aBQUFDpdX7Nq1C4888ghu3ryJFi1aVOvLwoULsWjRomrbv/jiCxiNxsZ820RERNQM/HhbwopTKlghYWYXC7oEuEW88ijFxcWYPHkybt++DT8/vzrbKjoCXJecHNsdlSEhIQ7bQ0JC5H05OTkIDg522K/RaBAYGOjQpm3bttWOYd9XUwCeP38+5s6dKz8vKChAREQERowY8asFbSwmkwkpKSkYPnw4tFqtS85JrLsSWHNlsO7KYN2V4Yq6jwZwZ8sPSD6YjSN3WmLupH4ePwrs6r/v9k/s68NtA7CS9Hq9/JXPlWm1Wpf/g6XEOYl1VwJrrgzWXRmsuzKcXffnhkbhiyM/IyM7H+k/FeCh9kFOO1dT4qq/7w05h9tOgxYaGgoAyM3Nddiem5sr7wsNDUVeXp7DfrPZjJs3bzq0qekYlc9BRERE9FuF+HnhyX4RAID3d5xTuDdUF7cNwG3btkVoaCh27NghbysoKEBaWhpiY2MBALGxscjPz0dGRobcZufOnbBarYiJiZHb7Nmzx+HC6JSUFHTq1KnGyx+IiIiI7tXMwe2hVUs4eOEGjly6qXR3qBaKBuCioiJkZmYiMzMTAHDx4kVkZmYiOzsbkiThhRdewP/+7/9i06ZNOHHiBJ5++mmEh4fLN8p16dIFI0eOxPTp03H48GHs378fSUlJePLJJxEeHg4AmDx5MnQ6HZ599llkZWXhX//6F5YuXepwjS8RERFRYwgPMOCJPrZR4GU7zv5Ka1KKotcAp6enY+jQofJzeyhNTExEcnIy5s2bhzt37mDGjBnIz8/HwIEDsXXrVnh5ecmvWb16NZKSkjBs2DCoVCpMmDABy5Ytk/f7+/tj+/btmDVrFvr06YOgoCAsWLCg1inQiIiIiH6L54e0x5fpP2Hv2es4mn0LvVrzE2d3o2gAHjJkCOqahU2SJCxevBiLFy+utU1gYCC++OKLOs/TvXt37N279577SURERFRfEYFGPN7rPnyV8TPe33kOK6f2U7pLVIXbXgNMRERE1FTNGtoBKgnY+UMeTl65rXR3qAoGYCIiIqJG1jbIG+N62O5Hen8nrwV2NwzARERERE6Q9EgHSBKwLSsXP+TU/0sayPkYgImIiIicoEOwL0Y/EAYAeH8n5wV2JwzARERERE6S9EgHAMCWE1dxLq9Q4d6QHQMwERERkZN0CfPDiOgQCAEs33Ve6e5QBQZgIiIiIif6wyNRAICNmVdw8fodhXtDAAMwERERkVN1u98fQzu1glUAH+zitcDugAGYiIiIyMn+MMw2Crz+6BX8dLNY4d4QAzARERGRk/Vu3QKDooJgtgqsSOW1wEpjACYiIiJyAfu1wOvSf8Iv+SUK98azMQATERERuUD/toGIaRsIk0XgI44CK4oBmIiIiMhF5lRcC7zmyE/IKyhVuDeeiwGYiIiIyEVi27dEn8gWKDdb8dGeC0p3x2MxABMRERG5iCRJ+EPFt8OtTruM60VlCvfIMzEAExEREbnQ4I6t0ON+f5SarPh470Wlu+ORGICJiIiIXMg2Cmy7Fvjzg5dw6065sh3yQAzARERERC42rEswosP8cKfcgpX7OQrsagzARERERC5W+Vrg5P2XcLvEpHCPPAsDMBEREZEC4ruGomOIDwrLzPj0wCWlu+NRGICJiIiIFKBSSUiquBb4k30XUVRmVrhHnoMBmIiIiEghY7qFoV0rb9wuMeGzg5eU7o7HYAAmIiIiUohaJWHWENu1wB/vvYjico4CuwIDMBEREZGCxvcMR+tAI27eKccXadlKd8cjuHUAXrhwISRJcnh07txZ3l9aWopZs2ahZcuW8PHxwYQJE5Cbm+twjOzsbIwZMwZGoxHBwcF4+eWXYTbzf1dERETkHjRqFWYNbQ8A+DD1AkpNFoV71Py5dQAGgK5du+Lq1avyY9++ffK+F198Ed988w3WrVuH1NRU/PLLL/jd734n77dYLBgzZgzKy8tx4MABfPrpp0hOTsaCBQuUeCtERERENXq81/24L8CA60VlWHuYo8DO5vYBWKPRIDQ0VH4EBQUBAG7fvo1PPvkE77zzDh555BH06dMHq1atwoEDB3Do0CEAwPbt23Hq1Cn885//RM+ePTFq1Cj86U9/wvLly1Fezm9dISIiIveg06jw3JC7o8BlZo4CO5NG6Q78mrNnzyI8PBxeXl6IjY3FkiVL0Lp1a2RkZMBkMiEuLk5u27lzZ7Ru3RoHDx7Egw8+iIMHD6Jbt24ICQmR28THx+O5555DVlYWevXqVeM5y8rKUFZWJj8vKCgAAJhMJphMrpmo2n4eV52PbFh312PNlcG6K4N1V0ZTqftjPULx/s6zyCkoxfaTVzGya8ivv8iNubruDTmPWwfgmJgYJCcno1OnTrh69SoWLVqEQYMG4eTJk8jJyYFOp0NAQIDDa0JCQpCTkwMAyMnJcQi/9v32fbVZsmQJFi1aVG379u3bYTQaf+vbapCUlBSXno9sWHfXY82Vwborg3VXRlOoezsvFXILVNi89yisl61Kd6dRuKruxcXF9W7r1gF41KhR8nr37t0RExODyMhIfPnllzAYDE477/z58zF37lz5eUFBASIiIjBixAj4+fk57byVmUwmpKSkYPjw4dBqtS45J7HuSmDNlcG6K4N1V0ZTqnvugcs4+N0ZCP9QjB7dU+nu/Caurrv9E/v6cOsAXFVAQAA6duyIc+fOYfjw4SgvL0d+fr7DKHBubi5CQ0MBAKGhoTh8+LDDMeyzRNjb1ESv10Ov11fbrtVqXf6Do8Q5iXVXAmuuDNZdGay7MppC3buE+wMAzl274/Z9rS9X1b0h53D7m+AqKyoqwvnz5xEWFoY+ffpAq9Vix44dl5UO7AAAGjhJREFU8v4zZ84gOzsbsbGxAIDY2FicOHECeXl5cpuUlBT4+fkhOjra5f0nIiIiqkvHEF8AwOUbxbwRzoncOgD/93//N1JTU3Hp0iUcOHAAjz/+ONRqNSZNmgR/f388++yzmDt3Lnbt2oWMjAxMmzYNsbGxePDBBwEAI0aMQHR0NJ566ikcO3YM27Ztw+uvv45Zs2bVOMJLREREpKRgXz38vDSwWAUuXLujdHeaLbe+BOLnn3/GpEmTcOPGDbRq1QoDBw7EoUOH0KpVKwDAu+++C5VKhQkTJqCsrAzx8fH44IMP5Ner1Wps3rwZzz33HGJjY+Ht7Y3ExEQsXrxYqbdEREREVCtJktAxxBfpl2/hx9xCdAlzzb1HnsatA/DatWvr3O/l5YXly5dj+fLltbaJjIzEli1bGrtrRERERE4RVRGAz+YWKd2VZsutL4EgIiIi8jQdQ3wAAD/mFirck+aLAZiIiIjIjdhvhDubxxFgZ2EAJiIiInIjURUjwJdv3EGpiTNBOAMDMBEREZEbaeWjR4BRC6sAzl/jKLAzMAATERERuRFJktAxuOIyCN4I5xQMwERERERuJoo3wjkVAzARERGRm7HfCPcjR4CdggGYiIiIyM3YR4DP5nEE2BkYgImIiIjcjH0EOPtmMUrKORNEY2MAJiIiInIzQT56BHrrIDgThFMwABMRERG5oahg3gjnLAzARERERG6IN8I5DwMwERERkRvqaL8RjiPAjY4BmIiIiMgNRdlHgDkTRKNjACYiIiJyQ/ZLIH66WYLicrPCvWleGICJiIiI3FCgtw5BPjoAwLk8XgfcmBiAiYiIiNxUVDBvhHMGBmAiIiIiN8Ub4ZyDAZiIiIjITck3wjEANyoGYCIiIiI3xbmAnYMBmIiIiMhN2S+BuJJfgqIyzgTRWBiAiYiIiNxUgFGHVr56ALwOuDExABMRERG5sbs3wvEyiMbCAExERETkxu5OhcYR4MbiUQF4+fLlaNOmDby8vBATE4PDhw8r3SUiIiKiOsk3wvHLMBqNxwTgf/3rX5g7dy7eeOMNfP/99+jRowfi4+ORl5endNeIiIiIasW5gBufxwTgd955B9OnT8e0adMQHR2NDz/8EEajEStXrlS6a0RERES1ss8FfPV2KQpKTQr3pnnQKN0BVygvL0dGRgbmz58vb1OpVIiLi8PBgwertS8rK0NZWZn8vKCgAABgMplgMrnmL579PK46H9mw7q7HmiuDdVcG666Mpl53owboFeGPAKMW+UWlMKiV7lH9uLruDTmPJIQQTuyLW/jll19w33334cCBA4iNjZW3z5s3D6mpqUhLS3Nov3DhQixatKjacb744gsYjUan95eIiIiIGqa4uBiTJ0/G7du34efnV2dbjxgBbqj58+dj7ty58vOCggJERERgxIgRv1rQxmIymZCSkoLhw4dDq9W65JzEuiuBNVcG664M1l0ZrLsyXF13+yf29eERATgoKAhqtRq5ubkO23NzcxEaGlqtvV6vh16vr7Zdq9W6/AdHiXMS664E1lwZrLsyWHdlsO7KcFXdG3IOj7gJTqfToU+fPtixY4e8zWq1YseOHQ6XRBARERFR8+cRI8AAMHfuXCQmJqJv377o378/3nvvPdy5cwfTpk1TumtERERE5EIeE4AnTpyIa9euYcGCBcjJyUHPnj2xdetWhISEKN01IiIiInIhjwnAAJCUlISkpCSlu0FERERECvKIa4CJiIiIiOwYgImIiIjIozAAExEREZFHYQAmIiIiIo/CAExEREREHsWjZoG4V0IIAA37ir3fymQyobi4GAUFBfzWGhdi3V2PNVcG664M1l0ZrLsyXF13e06z57a6MADXQ2FhIQAgIiJC4Z4QERERUV0KCwvh7+9fZxtJ1Ccmezir1YpffvkFvr6+kCTJJecsKChAREQEfvrpJ/j5+bnknMS6K4E1VwbrrgzWXRmsuzJcXXchBAoLCxEeHg6Vqu6rfDkCXA8qlQr333+/Iuf28/PjD6sCWHfXY82Vwborg3VXBuuuDFfW/ddGfu14ExwREREReRQGYCIiIiLyKOqFCxcuVLoTVDO1Wo0hQ4ZAo+GVKq7Eursea64M1l0ZrLsyWHdluGvdeRMcEREREXkUXgJBRERERB6FAZiIiIiIPAoDMBERERF5FAZgIiIiIvIoDMBuaPny5WjTpg28vLwQExODw4cPK92lJmXPnj0YO3YswsPDIUkSNmzY4LBfCIEFCxYgLCwMBoMBcXFxOHv2rEObmzdvIiEhAX5+fggICMCzzz6LoqIihzbHjx/HoEGD4OXlhYiICLz99ttOf2/uasmSJejXrx98fX0RHByMxx57DGfOnHFoU1pailmzZqFly5bw8fHBhAkTkJub69AmOzsbY8aMgdFoRHBwMF5++WWYzWaHNrt370bv3r2h1+vRoUMHJCcnO/vtua0VK1age/fu8iTzsbGx+O677+T9rLlrvPXWW5AkCS+88IK8jbVvfAsXLoQkSQ6Pzp07y/tZc+e5cuUKpkyZgpYtW8JgMKBbt25IT0+X9zfJ36uC3MratWuFTqcTK1euFFlZWWL69OkiICBA5ObmKt21JmPLli3ij3/8o/j6668FALF+/XqH/W+99Zbw9/cXGzZsEMeOHRPjxo0Tbdu2FSUlJXKbkSNHih49eohDhw6JvXv3ig4dOohJkybJ+2/fvi1CQkJEQkKCOHnypFizZo0wGAzio48+ctn7dCfx8fFi1apV4uTJkyIzM1OMHj1atG7dWhQVFcltZs6cKSIiIsSOHTtEenq6ePDBB8VDDz0k7zebzeKBBx4QcXFx4ujRo2LLli0iKChIzJ8/X25z4cIFYTQaxdy5c8WpU6fE+++/L9Rqtdi6datL36+72LRpk/j222/Fjz/+KM6cOSNee+01odVqxcmTJ4UQrLkrHD58WLRp00Z0795dzJkzR97O2je+N954Q3Tt2lVcvXpVfly7dk3ez5o7x82bN0VkZKSYOnWqSEtLExcuXBDbtm0T586dk9s0xd+rDMBupn///mLWrFnyc4vFIsLDw8WSJUsU7FXTVTUAW61WERoaKv7617/K2/Lz84Verxdr1qwRQghx6tQpAUAcOXJEbvPdd98JSZLElStXhBBCfPDBB6JFixairKxMbvPKK6+ITp06OfstNQl5eXkCgEhNTRVC2Gqs1WrFunXr5DanT58WAMTBgweFELb/uKhUKpGTkyO3WbFihfDz85PrPG/ePNG1a1eHc02cOFHEx8c7+y01GS1atBAff/wxa+4ChYWFIioqSqSkpIjBgwfLAZi1d4433nhD9OjRo8Z9rLnzvPLKK2LgwIG17m+qv1d5CYQbKS8vR0ZGBuLi4uRtKpUKcXFxOHjwoII9az4uXryInJwchxr7+/sjJiZGrvHBgwcREBCAvn37ym3i4uKgUqmQlpYmt3n44Yeh0+nkNvHx8Thz5gxu3brlonfjvm7fvg0ACAwMBABkZGTAZDI51L1z585o3bq1Q927deuGkJAQuU18fDwKCgqQlZUlt6l8DHsb/nwAFosFa9euxZ07dxAbG8uau8CsWbMwZsyYavVh7Z3n7NmzCA8PR7t27ZCQkIDs7GwArLkzbdq0CX379sV//Md/IDg4GL169cL//d//yfub6u9VBmA3cv36dVgsFocfTgAICQlBTk6OQr1qXux1rKvGOTk5CA4Odtiv0WgQGBjo0KamY1Q+h6eyWq144YUXMGDAADzwwAMAbDXR6XQICAhwaFu17r9W09raFBQUoKSkxCnvx92dOHECPj4+0Ov1mDlzJtavX4/o6GjW3MnWrl2L77//HkuWLKm2j7V3jpiYGCQnJ2Pr1q1YsWIFLl68iEGDBqGwsJA1d6ILFy5gxYoViIqKwrZt2/Dcc89h9uzZ+PTTTwE03d+r7vW9dETU5M2aNQsnT57Evn37lO6KR+jUqRMyMzNx+/ZtfPXVV0hMTERqaqrS3WrWfvrpJ8yZMwcpKSnw8vJSujseY9SoUfJ69+7dERMTg8jISHz55ZcwGAwK9qx5s1qt6Nu3L/785z8DAHr16oWTJ0/iww8/RGJiosK9u3ccAXYjQUFBUKvV1e5azc3NRWhoqEK9al7sdayrxqGhocjLy3PYbzabcfPmTYc2NR2j8jk8UVJSEjZv3oxdu3bh/vvvl7eHhoaivLwc+fn5Du2r1v3XalpbGz8/P4/9BajT6dChQwf06dMHS5YsQY8ePbB06VLW3IkyMjKQl5eH3r17Q6PRQKPRIDU1FcuWLYNGo0FISAhr7wIBAQHo2LEjzp07x7/vThQWFobo6GiHbV26dJEvP2mqv1cZgN2ITqdDnz59sGPHDnmb1WrFjh07EBsbq2DPmo+2bdsiNDTUocYFBQVIS0uTaxwbG4v8/HxkZGTIbXbu3Amr1YqYmBi5zZ49e2AymeQ2KSkp6NSpE1q0aOGid+M+hBBISkrC+vXrsXPnTrRt29Zhf58+faDVah3qfubMGWRnZzvU/cSJEw7/SKakpMDPz0/+xzc2NtbhGPY2/Pm4y2q1oqysjDV3omHDhuHEiRPIzMyUH3379kVCQoK8zto7X1FREc6fP4+wsDD+fXeiAQMGVJvW8scff0RkZCSAJvx71Sm31tE9W7t2rdDr9SI5OVmcOnVKzJgxQwQEBDjctUp1KywsFEePHhVHjx4VAMQ777wjjh49Ki5fviyEsE3XEhAQIDZu3CiOHz8uxo8fX+N0Lb169RJpaWli3759IioqymG6lvz8fBESEiKeeuopcfLkSbF27VphNBo9dhq05557Tvj7+4vdu3c7TFFUXFwst5k5c6Zo3bq12Llzp0hPTxexsbEiNjZW3m+fomjEiBEiMzNTbN26VbRq1arGKYpefvllcfr0abF8+XKPnqLo1VdfFampqeLixYvi+PHj4tVXXxWSJInt27cLIVhzV6o8C4QQrL0zvPTSS2L37t3i4sWLYv/+/SIuLk4EBQWJvLw8IQRr7iyHDx8WGo1GvPnmm+Ls2bNi9erVwmg0in/+859ym6b4e5UB2A29//77onXr1kKn04n+/fuLQ4cOKd2lJmXXrl0CQLVHYmKiEMI2Zcv//M//iJCQEKHX68WwYcPEmTNnHI5x48YNMWnSJOHj4yP8/PzEtGnTRGFhoUObY8eOiYEDBwq9Xi/uu+8+8dZbb7nqLbqdmuoNQKxatUpuU1JSIp5//nnRokULYTQaxeOPPy6uXr3qcJxLly6JUaNGCYPBIIKCgsRLL70kTCaTQ5tdu3aJnj17Cp1OJ9q1a+dwDk/zzDPPiMjISKHT6USrVq3EsGHD5PArBGvuSlUDMGvf+CZOnCjCwsKETqcT9913n5g4caLDXLSsufN888034oEHHhB6vV507txZ/OMf/3DY3xR/r0pCCNH448pERERERO6J1wATERERkUdhACYiIiIij8IATEREREQehQGYiIiIiDwKAzAREREReRQGYCIiIiLyKAzARERERORRGICJiIiIyKMwABMR1dOQIUPwwgsvKN0Np9qxYwe6dOkCi8Xi8nMLITBjxgwEBgZCkiRkZmb+puNt3boVPXv2hNVqbaQeElFzwQBMRFTJ1KlTIUlStce5c+ecfu42bdrI5zMajejWrRs+/vjjBh9HkiRs2LDhnvowb948vP7661Cr1QCA5ORkSJKELl26VGu7bt06SJKENm3a3NO5qtq6dSuSk5OxefNmXL16FQ888IC8b9q0aXj99dcBwOHPxdvbG1FRUZg6dSoyMjIcjjdy5EhotVqsXr26UfpHRM0HAzARURUjR47E1atXHR5t27Z1ybkXL16Mq1ev4uTJk5gyZQqmT5+O7777ziXn3rdvH86fP48JEyY4bPf29kZeXh4OHjzosP2TTz5B69atG+3858+fR1hYGB566CGEhoZCo9EAACwWCzZv3oxx48bJbVetWoWrV68iKysLy5cvR1FREWJiYvDZZ585HHPq1KlYtmxZo/WRiJoHBmAioir0ej1CQ0MdHvYR0cpu3bqFp59+Gi1atIDRaMSoUaNw9uxZALaP81u1aoWvvvpKbt+zZ0+EhYXJz/ft2we9Xo/i4mJ5m6+vL0JDQ9GuXTu88sorCAwMREpKirz/yJEjGD58OIKCguDv74/Bgwfj+++/l/fbR2Mff/zxaqOzGzduRO/eveHl5YV27dph0aJFMJvN8v61a9di+PDh8PLycnifGo0GkydPxsqVK+VtP//8M3bv3o3Jkyc7tD127BiGDh0KX19f+Pn5oU+fPkhPT5f379+/H0OGDIHRaESLFi0QHx+PW7duYerUqfjDH/6A7Ozsav0+cOAAtFot+vXrJ28LCAhAaGgo2rRpgxEjRuCrr75CQkICkpKScOvWLbnd2LFjkZ6ejvPnz4OIyI4BmIjoHk2dOhXp6enYtGkTDh48CCEERo8eDZPJBEmS8PDDD2P37t0AbGH59OnTKCkpwQ8//AAASE1NRb9+/WA0Gqsd22q14t///jdu3boFnU4nby8sLERiYiL27duHQ4cOISoqCqNHj0ZhYSEAW0AG7o6Q2p/v3bsXTz/9NObMmYNTp07ho48+QnJyMt5880352Hv37kXfvn1rfK/PPPMMvvzySzmsJycnY+TIkQgJCXFol5CQgPvvvx9HjhxBRkYGXn31VWi1WgBAZmYmhg0bhujoaBw8eBD79u3D2LFjYbFYsHTpUixevBj333+/Q78BYNOmTRg7diwkSarzz+PFF19EYWGhw38YWrdujZCQEOzdu7fO1xKRhxFERCRLTEwUarVaeHt7y48nnnhCCCHE4MGDxZw5c4QQQvz4448CgNi/f7/82uvXrwuDwSC+/PJLIYQQy5YtE127dhVCCLFhwwYRExMjxo8fL1asWCGEECIuLk689tpr8usjIyOFTqcT3t7eQqPRCAAiMDBQnD17ttb+WiwW4evrK7755ht5GwCxfv16h3bDhg0Tf/7znx22ff755yIsLEx+7u/vLz777DOHNqtWrRL+/v5CCCF69uwpPv30U2G1WkX79u3Fxo0bxbvvvisiIyPl9r6+viI5ObnGvk6aNEkMGDCg1vdS9Vh2UVFRYvPmzXW+PyGEKCkpEQDEX/7yF4ftvXr1EgsXLqz1vETkeTgCTERUxdChQ5GZmSk/arqG9PTp09BoNIiJiZG3tWzZEp06dcLp06cBAIMHD8apU6dw7do1pKamYsiQIRgyZAh2794Nk8mEAwcOYMiQIQ7Hffnll5GZmYmdO3ciJiYG7777Ljp06CDvz83NxfTp0xEVFQV/f3/4+fmhqKgI2dnZdb6nY8eOYfHixfDx8ZEf06dPx9WrV+VR3ZKSkmqXP1T2zDPPYNWqVUhNTcWdO3cwevToam3mzp2L3//+94iLi8Nbb73lcOmBfQS4IU6fPo1ffvmlXq8TQgBAtZFig8HgcJkJEREDMBFRFd7e3ujQoYP8qHzdbkN069YNgYGBSE1NdQjAqampOHLkCEwmEx566CGH1wQFBaFDhw4YNGgQ1q1bh9mzZ+PUqVPy/sTERGRmZmLp0qU4cOAAMjMz0bJlS5SXl9fZl6KiIixatMgh2J84cQJnz56VQ29QUJDD9bNVJSQk4NChQ1i4cCGeeuop+Sa1yhYuXIisrCyMGTMGO3fuRHR0NNavXw/AFkQbatOmTTVel1wT+388qt6wePPmTbRq1arB5yai5osBmIjoHnTp0gVmsxlpaWnyths3buDMmTOIjo4GYBuJHDRoEDZu3IisrCwMHDgQ3bt3R1lZGT766CP07dsX3t7etZ4jIiICEydOxPz58+Vt+/fvx+zZszF69Gh07doVer0e169fd3idVqutNo9v7969cebMGYdgb3+oVLZfBb169XII21UFBgZi3LhxSE1NxTPPPFNru44dO+LFF1/E9u3b8bvf/Q6rVq0CAHTv3h07duyo9XU12bhxI8aPH1+vtu+99x78/PwQFxcnbystLcX58+fRq1evBp2XiJo3BmAionsQFRWF8ePHY/r06di3bx+OHTuGKVOm4L777nMIbEOGDMGaNWvQs2dP+Pj4QKVS4eGHH8bq1asxePDgXz3PnDlz8M0338gzKURFReHzzz/H6dOnkZaWhoSEhGojq23atMGOHTuQk5Mjj+guWLAAn332GRYtWoSsrCycPn0aa9eulefWBYD4+Hjs27evzv4kJyfj+vXr6Ny5c7V9JSUlSEpKwu7du3H58mXs378fR44ckecQnj9/Po4cOYLnn38ex48fxw8//IAVK1ZUC/B2eXl5SE9Px6OPPlptX35+PnJycnD58mWkpKTgiSeewBdffIEVK1YgICBAbnfo0CHo9XrExsbW+b6IyLMwABMR3aNVq1ahT58+ePTRRxEbGwshBLZs2SLPegDYrgO2WCwO1/oOGTKk2rbaREdHY8SIEViwYAEA29y7t27dQu/evfHUU09h9uzZCA4OdnjN3//+d6SkpCAiIkIe+YyPj8fmzZuxfft29OvXDw8++CDeffddREZGyq9LSEhAVlYWzpw5U2t/DAYDWrZsWeM+tVqNGzdu4Omnn0bHjh3xn//5nxg1ahQWLVoEwDYyvH37dhw7dgz9+/dHbGwsNm7cWOOlFADwzTffoH///ggKCqq2b9q0aQgLC0Pnzp3x3HPPwcfHB4cPH642LduaNWuQkJBQ40wbROS5JGG/a4CIiDzeyy+/jIKCAnz00UdKdwXjxo3DwIEDMW/evHt6/fXr19GpUyekp6e77ItMiKhp4AgwERHJ/vjHPyIyMhJWq1XprmDgwIGYNGnSPb/+0qVL+OCDDxh+iagajgATERERkUfhCDAREREReRQGYCIiIiLyKAzARERERORRGICJiIiIyKMwABMRERGRR2EAJiIiIiKPwgBMRERERB6FAZiIiIiIPAoDMBERERF5lP8PJOFPKNXBQj4AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 800x400 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0HyX5y2NLdBu",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}